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Best features + Best algorithm = Accurate Predictions

                                                       Photo by Sam Balye on Unsplash

Every time you stumble upon a huge volume of data with thousands of features, you will be wondering what would be the best algorithm to get accurate predictions on this data, and whether to use all the features or reduce the feature space. Through this blog, I will take you through the steps in finding the good features through lasso regression and getting the right algorithm through a technique called stacking.

Selection of the best algorithm

The objective is to get accurate predictions of the target variable, with the most relevant explanatory variables. We will do that by applying machine learning models such as Random Forest, Lasso regression, and Gradient chúng tôi let us stack the output of these individual models and pass it to a ridge regressor to compute the final predictions. Stacking utilizes the strength of each individual model by using their output as input to the final model.

We compare the performance of the stacking regressor with individual models’ performance. The performance of stacking is usually close to the best model and sometimes it can outperform the prediction performance of each individual model. The plots at the end of this article show the performance of the individual regressors and the stacked regressor on a given data set.

Selection of the best features

In machine learning terminology, Least absolute shrinkage and selection operator (Lasso) is a regression analysis method that accomplishes both variable selection and regularization in order to enhance the prediction accuracy and interpretability of the model. It alters the model fitting process and selects only a subset of the covariates. It achieves this by forcing certain coefficients to be set to zero, and remove these coefficients in building the model.

Implementation

the performance of each model individually and the stack perormance. Follow along.

Step 1: Import all the libraries # let us import all the libraries # to handle datasets import numpy as np # for plotting import matplotlib.pyplot as plt # to divide train and test set from sklearn.model_selection import train_test_split # feature scaling from sklearn.preprocessing import MinMaxScaler #to buid models from sklearn.linear_model import Lasso from sklearn.feature_selection import SelectFromModel # models for Stacking from sklearn.ensemble import GradientBoostingRegressor from sklearn.ensemble import RandomForestRegressor from sklearn.ensemble import StackingRegressor from sklearn.linear_model import LassoCV from sklearn.linear_model import RidgeCV # to evaluate the model from sklearn.metrics import mean_squared_log_error from sklearn.metrics import mean_squared_error,r2_score import math #to find training time of the model import time # to visualise al the columns in the dataframe pd.pandas.set_option('display.max_columns', None) import warnings warnings.simplefilter(action='ignore') Step 2: Load dataset

Python Code:



Step 3: Data Engineering

Data needs to be engineered to handle:

Treat missing values

Categorical variables: Remove rare labels

Categorical variables encoding

Engineer temporal variables

Treat non-Gaussian distributed variables

Feature scaling

Before beginning to engineer our features, we separate the data into training and testing set. Because when we engineer features, some techniques learn parameters from data. It is important to learn these parameters only from the train set to avoid over-fitting. Further, we need to set the seed wherever we expect randomness.

# Let's separate into train and test set # Remember to set the seed (random_state for this sklearn function) X_train, X_test, y_train, y_test = train_test_split(data,data['SalePrice'],test_size=0.25, random_state=0) X_train.shape, X_test.shape

We will find the missing values in numerical variables, and replace them with the mode.

replace missing values with mode # make a list with the numerical variables that contain missing values for var in vars_with_na: # calculate the mode using the train set mode_val = X_train[var].mode()[0] # replace missing values by the mode # (in train and test) X_train[var] = X_train[var].fillna(mode_val) X_test[var] = X_test[var].fillna(mode_val)

Make a list of the categorical variables that contain missing values and replace them with the label ‘Missing’

# make a list of the categorical variables that contain missing values # replace missing values with new label: "Missing" X_train[vars_with_na] = X_train[vars_with_na].fillna('Missing') X_test[vars_with_na] = X_test[vars_with_na].fillna('Missing')

Categorical-Removing rare labels

First, we will isolate those categories within variables that are present in less than 1% of the observations. That is, all values of categorical variables that are shared by less than 1% of houses will be named as “Rare”.

# let's capture the categorical variables in a list cat_vars = [var for var in X_train.columns if X_train[var].dtype == 'O'] def find_frequent_labels(df, var, rare_perc): # find_frequent_labels function finds the labels that are shared by more than # a certain % of the houses in the dataset df = df.copy() tmp = df.groupby(var)['SalePrice'].count() / len(df) for var in cat_vars: # find the frequent categories frequent_ls = find_frequent_labels(X_train, var, 0.01) # replace rare categories by the string "Rare" X_train[var] = np.where(X_train[var].isin(frequent_ls), X_train[var], 'Rare') X_test[var] = np.where(X_test[var].isin(frequent_ls), X_test[var], 'Rare')

Categorical variable encoding

Next, we will write a small function that assigns discrete values to the strings of the variables. For instance, the smaller value corresponds to the category that shows a smaller mean house sale price.

def replace_categories(train, test, var, target): # order the categories in a variable from that with the lowest # house sale price, to that with the highest ordered_labels = train.groupby([var])[target].mean().sort_values().index # create a dictionary of ordered categories to integer values ordinal_label = {k: i for i, k in enumerate(ordered_labels, 0)} # use the dictionary to replace the categorical strings by integers train[var] = train[var].map(ordinal_label) test[var] = test[var].map(ordinal_label) for var in cat_vars: replace_categories(X_train, X_test, var, 'SalePrice')

Engineer temporal variables

There are 4 variables that refer to the years in which the house or the garage was built or remodeled. We will capture the time elapsed between those variables and the year in which the house was sold:

def elapsed_years(df, var): # capture difference between the year variable # and the year in which the house was sold df[var] = df['YrSold'] - df[var] return df for var in ['YearBuilt', 'YearRemodAdd', 'GarageYrBlt']: X_train = elapsed_years(X_train, var) X_test = elapsed_years(X_test, var)

Treat non-gaussian distributed variables

Some variables show skewed distribution. We will log transform the positive numerical variables in order to get a more Gaussian-like distribution. This will help linear machine learning models.

for var in ['LotFrontage', 'LotArea', '1stFlrSF', 'GrLivArea', 'SalePrice']: X_train[var] = np.log(X_train[var]) X_test[var] = np.log(X_test[var])

Feature Scaling

For use in linear models, features need to be either scaled or normalized. We will scale features to the minimum and maximum values.

# capture all variables in a list # except the target and the ID train_vars = [var for var in X_train.columns if var not in ['Id', 'SalePrice']] # create scaler scaler = MinMaxScaler() # fit the scaler to the train set scaler.fit(X_train[train_vars]) # transform the train and test set X_train[train_vars] = scaler.transform(X_train[train_vars]) X_test[train_vars] = scaler.transform(X_test[train_vars]) print(X_train.isnull().sum().any(),X_test.isnull().sum().any())

We finished the formal feature engineering steps. You can extend these feature engineering steps. For example removal of outliers etc.

Step 4: Feature Selection

We will select variables using the Lasso regression: Lasso has the property of setting the coefficient of non-informative variables to zero. This way we can identify those variables and remove them from our final model. In the following cells, we will select a group of variables, the most predictive ones, to build our machine learning model.

# capture the target (notice that the target is log transformed) y_train = X_train['SalePrice'] y_test = X_test['SalePrice'] # drop unnecessary variables from our training and testing sets X_train.drop(['Id', 'SalePrice'], axis=1, inplace=True) X_test.drop(['Id', 'SalePrice'], axis=1, inplace=True)

Let’s go ahead and select a subset of the most predictive features. There is an element of randomness in the Lasso regression, so remember to set the seed.Select a suitable alpha (the equivalent of penalty).The bigger the alpha the less number of features will be selected.

sel_= SelectFromModel(Lasso(alpha=0.005,random_state=0)) # train Lasso model and select features sel_.fit(X_train,y_train) # let's print the number of total and selected features selected_feats = X_train.columns[(sel_.get_support())] # let's print some stats print('Total features: {}'.format((X_train.shape[1]))) print('selected features: {}'.format(len(selected_feats))) print('features with coefficients shrank to zero: {}'.format(np.sum(sel_.estimator_.coef_== 0)))

25 out of 79 features are chúng tôi us have a look at the important features.

#let's look at the feature importance importance = pd.Series(np.abs(lin_model.coef_.ravel())) importance.index = selected_feats importance.sort_values(inplace=True, ascending=False) importance.plot.bar(figsize=(10,6)) plt.ylabel('Lasso Coefficients') plt.title('Feature Importance') Step 5: Build models

Extract the selected features.

X_train=X_train[selected_feats] X_test=X_test[selected_feats] print(X_train.shape,X_test.shape)

adding the models in the stack.

# The parameters inside the models can be varied params = {'n_estimators': 500, 'max_depth': 4, 'min_samples_split': 5, 'learning_rate': 0.01, 'loss': 'ls'} GB_model= GradientBoostingRegressor(**params) lin_model = Lasso(alpha=0.005, random_state=0) RF_model = RandomForestRegressor(n_estimators=400,random_state=0) # Get these models in a list estimators = [('Random Forest', RF_model), ('Lasso', lin_model), ('Gradient Boosting', GB_model)] #Stack these models with StackingRegressor stacking_regressor = StackingRegressor(estimators=estimators, final_estimator=RidgeCV()) Step 6: Compare the performance 

We will compare the performance with the help of scatter plots

def plot_regression_results(ax, y_true, y_pred, title, scores, elapsed_time): """Scatter plot of the predicted vs true targets.""" ax.plot([y_true.min(), y_true.max()], [y_true.min(), y_true.max()], '--r', linewidth=2) ax.scatter(y_true, y_pred, alpha=0.2) ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) ax.get_xaxis().tick_bottom() ax.get_yaxis().tick_left() ax.spines['left'].set_position(('outward', 10)) ax.spines['bottom'].set_position(('outward', 10)) ax.set_xlim([y_true.min(), y_true.max()]) ax.set_ylim([y_true.min(), y_true.max()]) ax.set_xlabel('True_Price') ax.set_ylabel('Predicted_Price') extra = plt.Rectangle((0, 0), 0, 0, fc="w", fill=False, edgecolor='none', linewidth=0) ax.legend([extra], [scores], loc='upper left') title = title + 'n Evaluation in {:.2f} seconds'.format(elapsed_time) ax.set_title(title) fig, axs = plt.subplots(2, 2, figsize=(9, 7)) axs = np.ravel(axs) errors_list=[] for ax, (name, est) in zip(axs, estimators + [('Stacking Regressor',                                                stacking_regressor)]):     start_time = time.time()     model = est.fit(X_train, y_train)                           elapsed_time = time.time() - start_time         pred = model.predict(X_test)     errors = y_test - model.predict(X_test)     errors_list.append(errors)     test_r2= r2_score(np.exp(y_test), np.exp(pred))         test_rmsle=math.sqrt(mean_squared_log_error(y_test,pred))     plot_regression_results(ax,y_test,pred,name,(r'$R^2={:.3f}$' + 'n' +                              r'$RMSLE={:.3f}$').format(test_r2,test_rmsle),elapsed_time) plt.tight_layout() plt.subplots_adjust(top=0.9) plt.show()

By looking at the plots, we observe that the gradient boosting model performs well, and the stacking regressor is closer to the gradient boosting model in performance.

Let us see the distribution of errors of each of these models.

titles = ['Random_Forest','Lasso','Gradient_boosting','Stacked_regressor'] f,a = plt.subplots(2,2) a = a.ravel() for idx,ax in enumerate(a): ax.hist(errors_list[idx]) ax.set_title(titles[idx]) plt.tight_layout()

#let's look at the feature importance importance = pd.Series(np.abs(lin_model.coef_.ravel())) importance.index = selected_feats importance.sort_values(inplace=True, ascending=False) importance.plot.bar(figsize=(10,6)) plt.ylabel('Lasso Coefficients') plt.title('Feature Importance')

The distribution of the errors follows quite closely a gaussian distribution. That suggests that our models are doing a good job in making predictions.

Thanks for reading. Like, share, and write your thoughts.

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How To Choose A Proxy Provider?

If you’re opening a new business and you want to get the most out of your digital marketing efforts, getting a proxy can help you a lot. For one, you’ll be able to monitor prices, competitors, and other details to get valuable insights into the latest trends and identify gaps you can use to grow your business.

However, finding the right proxy for your needs can be very difficult as thousands of providers are all claiming how their services are the best. Stay with us, and we’ll explain what a proxy service is exactly, why you should invest in web scraping, and how to find the best service for your needs.

Do You Know What Proxies Are?

Think about proxies as the middle-man between your device and the internet. Every time you want to find any type of information online, your device sends a request, and the servers respond by sending you the information you requested.

Each device has its own IP address, which is a digital address needed for the servers to identify who made the request. Every user has a unique IP address which is their online ID, in a sense.

The problem is that if you want to browse a competitor’s website using a web scraper on your quest to find the best prices for products and services, your IP can be identified and banned from accessing the site in the future.

Also read: What Is Forex Trade? 5 Untold Forex Trading Benefits + Expert Tips For Higher Forex Profit

How a Business can use a Proxy Service

Running an online business will put you against tough competition, so you’ll have to use everything you can to win over a portion of the market. Proxies can help you a lot if you know how to use them. There is no doubt that your business will get a set of useful benefits from using a proxy. Here’s a quick overview of the biggest benefits of using proxies for your business:

Extra Security – Proxies can help you protect your website or servers from hacker attacks. They add another extra layer of protection that makes it much harder for hackers to locate your network and breach your security.

Anonymity – Running an online business means that you’ll spend a lot of time looking at your competitor’s websites. You’ll want to know what they are doing to be so successful, and your competition will try to stop you from gathering that information. Your connection will always stay anonymous with proxies, so you won’t have to worry about getting banned.

Limit online visibility – Proxies can also run on local networks, and you can use them to control some online activities. You can create a list of servers users can open and block the undesired content.

The Process of Web Scraping

Web scraping is a process of gathering and extracting specific information you can later use to improve your business. It is done with special tools designed to help you collect specific data and extract it in a readable format. All you have to do is to find a website you want to scrape, include a keyword or phrase you want it to find, and wait for the tool to do its magic.

It’s a very powerful method of gathering high-quality information, and it can help you create the best offer that attracts the most customers.

How to Find a Reliable Proxy Service

Also read: 10 Types of Developer Jobs: IT Jobs

Conclusion

Proxies are completely transforming the way we use the internet. They are very powerful tools that can help you find and extract valuable information without anyone knowing. If you’re running a business, getting a proxy service will help you extend your reach and keep a close eye on your competition, among other things. Give it a try, and you’ll see exactly why you need proxies and web scrapers.

Doma Stankevičiūtė

Doma is a Content Manager with experience of over three years. Currently, she is working at Oxylabs, a leading proxy service provider. She has a wide interest in technology and data analysis. Thus she mostly writes about said topics. She believes that quality content is the key to a successful website.

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How To Choose An Amd Cpu

In the last few years, AMD has launched some awesome CPUs. Names like Ryzen 3 and Ryzen 5 hint at the idea that they’re equivalent to Intel i3 and Intel i5.

And that’s true, for the most part. But this won’t be an article about AMD vs Intel. Instead, it will be a guide about how to buy the best AMD CPU for your usage. And just like it doesn’t make sense to buy a super car just to go grocery shopping, it doesn’t make sense to buy a 16 core AMD Ryzen Threadripper for casual web browsing or office work. And, contrary to what some might believe, it is often not the best choice for gaming either, and you will see why later in this article.

How to Understand AMD CPU Names How to Interpret AMD CPU Model Number

Consider the following model: AMD Ryzen 7 3800X. What does “3800X” mean?

The first digit, “3,” tells you the generation number. So “3800X” is a third generation CPU, an improved version of the first and second generations.

The second digit, “8,” tells you the performance level. This means that 3800 performs better than a 3700. Usually, models with 6 to 9 as the second digit are found in desktop CPUs and below 6 are found in laptops since they consume less power but also perform worse.

The next two digits may signal minor differences such as slight increases in the frequency they operate.

The last suffix, “X” in this case, is optional.

X signals high-performance, higher clock speeds than the equivalent model without an X suffix.

G signals low-power desktop with integrated GPU.

H signals higher-power mobile device, e.g., laptop. (“high power” might suggest performance, but they’re still slower than standard desktop CPU.)

U signals standard power lower clocked, for mobile devices

M signals very low-power consumption, which also means very low performance.

What AMD CPU Is Best for You?

To answer this question, you first have to decide what kind of workload you throw at your computer most often.

To browse the Web, watch YouTube, Netflix and such, a Ryzen 3 is more than enough. If you are getting a laptop, though, try to pick a Ryzen 5, since the power-efficient processors are so much slower than the ones for desktops.

How to Choose Best AMD CPU for Gaming

If you play games, a high clock speed for the CPU is much more important than the core count. You should aim for at least six cores and then look for the CPU with the highest number of GHz you can find and afford. You might also focus on models with the “X” suffix, as those have increased clock speeds over the base models. The Threadripper series might seem like the best choice for gaming, but it isn’t since most of those models have lower clock speeds when compared to the best CPUs in the Ryzen 7 or 9 series.

You can read more about why CPU clock speed matters in games, in the last part of this article. An easy way to find a gaming CPU is to consult this list of processors that currently have the best benchmark results in single-thread performance.

You can see in the above picture how one of the best choices for a gaming CPU on that date is Ryzen 5 3600X, because it’s by far the cheapest in the list with very similar performance to all the others. AMD Ryzen 7 3800X is much more expensive because it has more cores. But the two CPUs might get almost identical frame rates in a game like GTA V.

Best AMD CPUs for Content Creators

So when is Threadripper a good choice? When you need lots and lots of parallelism. This is the case for video editing, photography/graphics work, editing, producing and mixing music, and so on. You should also buy a Threadripper if you often use virtual machines. Additionally, they’re great if you intend to use the machine as a server.

Conclusion

Often, you will find two or three models at a similar price and won’t be sure which one to choose. In that case, just google something like “amd ryzen 3800x benchmark” and consult the result from “cpubenchmark.net,” as that will show you a total score (how all cores perform when splitting a big task into small tasks) and a single-thread score, how fast a single core is.

If money is tight, you can also buy a CPU that is one generation behind, as you won’t lose a lot of performance but will save a lot on cost.

Happy CPU hunting!

Alexandru Andrei

Fell in love with computers when he was four years old. 27 years later, the passion is still burning, fueling constant learning. Spends most of his time in terminal windows and SSH sessions, managing Linux desktops and servers.

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How To Choose The Right Haircut For Your Face Shape

Choosing the right hairstyle can enhance your facial features and complement your overall look. It’s important to consider your face shape when deciding on a haircut or style. There are six main face shapes: oval, round, square, heart, diamond, and long, each with their own unique features and recommended hairstyles.

Identifying Your Face Shape

Identifying your face shape is the first step in choosing the right hairstyle. Here are some tips for determining your face shape −

Look at your jawline

Is it narrow and pointed (heart- or diamond-shaped), rounded (round or oval), or angular (square or rectangular)?

Measure your forehead

Use a tape measure to measure the width of your forehead at its widest point. If it’s wider than your cheekbones and jawline, you likely have a heart- or diamond-shaped face. If it’s about the same width as your cheekbones and jawline, you likely have an oval or round face. If it’s narrower than your cheekbones and jawline, you likely have a square or rectangular face.

Measure your cheekbones

Use a tape measure to measure the width of your cheekbones at their widest point. If they’re wider than your forehead and jawline, you likely have a heart- or diamond-shaped face. If they’re about the same width as your forehead and jawline, you likely have an oval or round face. If they’re narrower than your forehead and jawline, you likely have a square or rectangular face.

Measure the length of your face

Use a tape measure to measure the distance from the centre of your hairline to the tip of your chin. If it’s longer than the width of your face, you likely have a long face. If it’s about the same length as the width of your face, you likely have an oval or round face.

By using these tips, you can determine your face shape and choose the right hairstyle that enhances your features.

Choosing The Right Hair Length for Your Face Shape

Choosing the right hair length for your face shape can make a big difference in how your hair frames your face and complements your features. For round faces, a length that falls just below the chin can help elongate the face and create the illusion of length. For square faces, a length that falls just below the jawline can help soften the angles of the face and create a more proportional look. Heart-shaped faces can be balanced out with a length that falls at or below the chin, while diamond-shaped faces can benefit from a length that also falls at or below the chin.

For long faces, a length that hits at or above the shoulders can help add width and volume to the face, creating a more balanced look. Ultimately, the most important thing is to choose a hairstyle and length that you feel comfortable and confident with, and that makes you feel your best.

Hairstyles for Oval Faces

Oval faces are versatile and can pull off a variety of hairstyles. Here are some hairstyles that work well for oval faces −

Long layers − Long, layered hair can add dimension to an oval face and accentuate its length.

Side-swept bangs − Side-swept bangs can help balance out an oval face and draw attention to the eyes.

Bob haircut − A chin-length bob can accentuate an oval face’s symmetry and make it appear more angular.

Updo − An updo that pulls hair away from the face can showcase an oval face’s proportions and emphasize its natural shape.

Pixie cut − A short, textured pixie cut can highlight an oval face’s delicate features and create a bold look.

Hairstyles for Round Faces

Long layers − Long layers that hit below the shoulders can help elongate a round face and create the illusion of length.

Side-swept bangs − Side-swept bangs can help elongate the face and draw attention to the eyes.

Angled bob − An angled bob that’s longer in the front and shorter in the back can help create a more angular look for a round face.

High ponytail − A high ponytail can elongate the face and add height to the top of the head.

Beachy waves − Soft, beachy waves that fall below the chin can help create the illusion of length for a round face.

Hairstyles for Square Faces

Soft layers − Soft layers can help soften the angles of a square face and add movement and dimension.

Side-swept bangs − Side-swept bangs can help soften the corners of a square face and draw attention to the eyes.

Shoulder-length bob − A shoulder-length bob that hits at the jawline can help soften the squareness of the face.

Loose curls − Loose, voluminous curls can help soften the angles of a square face and add texture.

Pixie cut − A textured pixie cut with soft, wispy edges can help soften the angles of a square face and create a more feminine look.

Hairstyles for Heart-Shaped Faces

Side-swept bangs − Side-swept bangs can help balance out a heart-shaped face and draw attention to the eyes.

Long layers − Long, face-framing layers can help soften the forehead and accentuate the jawline of a heart-shaped face.

Bob haircut − A chin-length bob with side-swept bangs can help balance out a heart-shaped face and create a more proportional look.

Pixie cut − A short, textured pixie cut can highlight a heart-shaped face’s delicate features and create a bold look.

Half-up hairstyle − A half-up hairstyle that pulls hair away from the forehead can showcase a heart-shaped face’s natural shape and proportions.

Hairstyles for Diamond-Shaped Faces

Pixie cut − A short, textured pixie cut can highlight a diamond-shaped face’s delicate features and create a bold look.

Bob haircut − A chin-length bob with soft layers can help balance out the narrow forehead and jawline of a diamond-shaped face.

Side-swept bangs − Side-swept bangs can help balance out a diamond-shaped face and draw attention to the eyes.

Updo − An updo that pulls hair away from the face can showcase a diamond-shaped face’s unique features and create a sleek, elegant look.

Shoulder-length waves − Soft, voluminous waves that hit at the shoulders can help balance out a diamond-shaped face and add texture and movement.

Hairstyles for Long Faces

Blunt bangs − Blunt bangs can help shorten the appearance of a long face and draw attention to the eyes.

Shoulder-length layers − Layers that hit at or above the shoulders can help add width and volume to a long face.

Wavy bob − A wavy bob that hits at the chin can help create the illusion of width and balance out a long face.

Pixie cut − A textured pixie cut can help break up the length of a long face and create a more proportional look.

Side part − A deep side part can help create the illusion of width and balance out a long face.

Remember, these are just suggestions; the most important thing is to choose a hairstyle that makes you feel confident and comfortable in your own skin.

Conclusion

In conclusion, choosing the right hairstyle for your face shape can help highlight your best features and create a flattering look that enhances your natural beauty. Whether you have an oval, round, square, heart-shaped, or diamond-shaped face, there are many hairstyles and lengths to choose from that can help balance out your features and create a more proportional look.

By identifying your face shape and exploring different hairstyles and lengths, you can find a style that makes you feel confident and comfortable and that complements your unique features. Remember, the most important thing is to choose a hairstyle that makes you feel good and that reflects your personal style and preferences

How To Choose A 401(K) Plan

What types of 401(k) plans are there?

You can find a complete breakdown of 401(k) plans on the IRS website, but these are some of the most common types of 401(k) plans you can expect to find during your search.

Editor’s note: Looking for an employee retirement plan for your business? Fill out the below questionnaire to have our vendor partners contact you with free information.

Traditional 401(k) plan 

Considered the most flexible of the plans, a traditional 401(k) allows employees to make pretax contributions through payroll deductions. Traditional 401(k) plans are often offered with an employer match program. These contributions are not always vested, meaning that employees do not own the matching contributions until they meet certain provisions.

Contribution limits: In 2023, the annual contribution limit is $20,500, with an additional $6,500 “catch-up” for employees aged 50 and older.

Employer match: This contribution is not automatically vested, and the amount depends on the employee’s annual contribution and the employer’s own plan.

Safe harbor 401(k) plan 

This plan is similar to the traditional plan, except it mandates that employer contributions be vested as soon as they are made. There are three types of safe harbor plan, two of which have employer match provisions. Safe harbor plans are also not subject to the nondiscrimination tests that traditional 401(k) plans must go through.

Contribution limits: In 2023, the annual contribution limit is $20,500, with an additional $6,500 “catch-up” for employees aged 50 and older.

Employer match: Yes, it is guaranteed vested; the amount depends on the employee’s annual contribution and the employer’s own plan.

SIMPLE 401(k) plan

The Savings Incentive Match Plan for Employees (SIMPLE) 401(k) is best used as a startup retirement savings plan for companies that do not have a plan in place. Only businesses with fewer than 100 employees can offer this plan.

Contribution limits: In 2023, the annual contribution limit is $14,000, with an additional $3,000 “catch-up” for employees aged 50 and older.

Employer match: Yes, up to 2% nonelective contribution or up to 3% matching contribution.

Roth 401(k) plan

This plan is funded with post-tax income, so money saved is not subject to any federal or state taxes as long as the investor reaches the age of 59.5 before withdrawal.

Contribution limits: In 2023, the annual contribution limit is $20,500, with an additional $6,500 “catch-up” for employees aged 50 and older.

Employer match: Yes, pretax.

Solo 401(k) plan

A solo 401(k) plan for self-employed individuals or businesses with only one employee offers contractors and sole proprietors a retirement savings option as well. Self-employed individuals can choose the traditional or Roth structure for their solo 401(k) plans.

Contribution limits: In 2023, the annual contribution limit is $61,000, with an additional $6,500 “catch-up” for employees aged 50 and older.

Employer match: Not applicable.

Profit-sharing plans

With a profit-sharing plan, an employer sets aside a portion of its pretax income to share among its employees. This plan type gives you flexibility in how much money you contribute. There are several varieties of profit-sharing plans under this umbrella, including pro rata plans, new comparability plans and age-weighted profit-sharing plans.

Contribution limits: For 2023, the annual contribution limit for profit-sharing plans is $61,000 or 100% of the employee’s salary, whichever amount is lower.

Employer match: Yes; the amount varies.

403(b) plans

A 403(b) retirement plan is a tax-sheltered account reserved for teachers that is sometimes also used by eligible not-for-profit organizations, including religious ones. Contributions are pretax, and earnings are not taxed until they are distributed.

Contribution limits: In 2023, the annual contribution limit is $20,500, with an additional $6,500 “catch-up” for employees aged 50 and older.

Employer match: Yes, pretax.

There are many other types of 401(k) plans, but the more complex they become, according to Meadows, the less likely they are to fit small businesses. “Larger companies with a 401(k) may want a special variety for their type of business,” he said. “However, small businesses will likely want to keep it simple to avoid any complicated compliance worries.”

He also noted that it’s important to know why the plan is being established in order to determine which one is right for your business. “Is this a plan for the owner to put as much money as possible away for their own future, or is this primarily a benefit for employees? Without a doubt, this is a great decision for any company that expects to put away more than [the IRA limit] per year.”

Did You Know?

You can borrow against a 401(k) without incurring tax penalties for early withdrawal, but you will have to pay the borrowed amount back through future contributions.

What should you consider when choosing a plan, and when should you get one?

Meadows said that small businesses should want to provide the most robust 401(k) plan that the business can afford.

“Today, there are more and more providers helping small businesses avoid high-cost funds and access manageable monthly administration fees,” he continued. “This may vary from business to business, but the sooner you can set up a 401(k) plan, the better.”

Even though a 401(k) plan makes the most sense for small businesses, there are many things to consider as a business owner when considering offering your employees a retirement plan. Here are a few that Smith laid out:

Income and age of owner(s)

Income and age of the employees

The time frame for which business will offer the plan

The budget and resources that are available to manage the retirement plan

“Generally speaking, any business that seeks to provide a relatively simple and low-cost plan may consider a 401(k),” Smith said.

Tip

Think about the size of your company and what you can afford in terms of contributions and management fees when exploring the types of 401(k) accounts.

The future of 401(k) plans 

Social Security funds continue to be depleted and workers are increasingly concerned about the future of retirement.

Currently, one quarter of Americans 65 and older receive 90% of their income from Social Security payments. However, the 2023 Social Security Trustees report found that, without any intervention, funds will run out by the mid-2030s. At that time, the report estimates Social Security funds will only pay 78% of scheduled benefits.

Roger Lee, co-founder of Human Interest, agrees that America has a looming retirement crisis. 

Roughly half of Americans are saving 10% of their annual income or less toward all of their financial goals, falling short of what is recommended for retirement.

“While it’s essential to have a discussion about financial responsibility and planning, it’s also important to recognize that many workers don’t have access to 401(k) plans, which has become the dominant means of saving for retirement.”

However, if you are one of the lucky people who have access to a 401(k), these plans have become the forerunner in addressing retirement needs.

“[Social Security] and pension plans are of the past,” said Brian Menickella, co-founder of financial services firm The Beacon Group of Companies. He thinks the financial future of retirement is bright, even with the continued concern around Social Security.

Stella Morrison contributed to the writing and research in this article. Source interviews were conducted for a previous version of this article.

Best Browser For Duckduckgo: 6 Privacy Picks To Choose From

Best Browser for Duckduckgo: 6 Privacy Picks to Choose From DuckDuckGo is a search engine that takes user privacy very seriously

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If you don’t like the idea that giants like Google or even Bing track your search history, you’ll love DuckDuckGo. 

To get the most of this search engine, match it with an equally privacy-focused DuckDuckGo browser.

Struggling with various browser issues? Try a better option: Opera One

You deserve a better browser! Over 300 million people use Opera One daily, a fully-fledged navigation experience coming with various built-in packages, enhanced resource consumption, and great design.

Here’s what Opera One can do:

Optimize resource usage: Opera One uses your Ram more efficiently than Brave

AI and User Friendly: New feature directly accessible from the sidebar

Gaming friendly: Opera GX is the first and best browser for gamers

⇒ Get Opera One

DuckDuckGo is popular among people who take their privacy seriously and don’t want giants like Google or even Bing to track their search history.

A DuckDuckGo browser is equally important. And if you’re just scratching the surface when it comes to this topic, you may be wondering what is DuckDuckGo?

Others may have more of a dilemma and ponder on things like: is DuckDuckGo a browser or a search engine? We’re hoping that our explanations below will help to answer all of these questions.

Does DuckDuckGo make a web browser?

To start with, DuckDuckGo is a search engine that takes user privacy very seriously. While all search engines claim they respect user privacy, it is a well-known fact that collected data is what keeps these search giants running.

DuckDuckGo, on the other hand, does not track user data, thus being one among the few fully private search engines.

So how to use DuckDuckGo? It’s simple, just like you would with any other search engine such as Google, for instance.

It is recommended to use a DuckDuckGo browser, though. Using a DuckDuckGo desktop browser with better privacy features can empower users to take control of their personal information online without any tradeoffs.

By teaming up with a DuckDuckGo browser for Windows, you can enhance the impact of the private search engine even more.

What is the downside of DuckDuckGo?

➡ Fewer services – DuckDuckGo can’t compare to a search engine like Google when it comes to services

➡ Less customization – You can’t sync all your accounts and services with it

➡ No personalization or autosuggestions – This is a pro and con at the same time because the personalization and the suggestions within the search come from tracking your information as Google does

That being said, let’s go and see what are the best privacy-focused browsers for DuckDuckGO. DuckDuckGo’s desktop browser compatibility is very wide but we have picked the very best of them for you.

Opera One Browser is a popular web browser for the Windows platform. Recently, it received a complete design overhaul along with some fancy features that make it the best privacy browser for DuckDuckGo.

The latest version comes with a free VPN, a fast ad blocker, Web 3 support, and a lot more control over your browsing experience.

You can select a dark or light theme, use Messenger and WhatsApp without leaving the browser as well as store and use Cryptocurrency in the built-in Crypto wallet.

Opera One also comes with extension support, a built-in screenshot tool, and other security features such as HTTP redirection, etc.

Opera One

Enhance your privacy with the ultimate DuckDuckGo browser with a built-in free VPN.

Free Download Now

UR Browser comes with a well-polished UI and a ton of privacy and security features. Chromium-based UR offers similar functionalities to Google Chrome and some additional features on top, we dare say.

Its privacy features include an inbuilt VPN with different servers for you to choose from when launching a private connexion.

UR Browser

It’s like having your own digital bodyguard and security assistant.

Free Visit website

Are you wondering what is the match for DuckDuckGo to get more privacy? AVG browser is a straight fit for boosting online privacy.

This popular browser is used by many for complete web security, as it can offer you browsing fingerprint masking and a VPN shield to stop any trackers.

Not only that, you can use helpful functionalities such as the Privacy Cleaner to remove history data, forced HTTPS encryption, adware defense, or antivirus shield.

It’s essential to know that you have zero tracking scripts or cookies that gather personal data while you access web pages.

AVG

Don’t allow any tracking or data collecting with this browser and DuckDuckGo engine.

Free Visit website

After Google Chrome, Mozilla Firefox is probably the most popular browser available for Windows computers. Similar to Opera One, Firefox also received a major overhaul to its design in the recent update along with enhanced speed and resource management.

Firefox allows you to sync your browsing data across devices by creating an account. The popular add-on/extension support has now improved with a more strict approach to applicable add-ons.

The Private browsing mode now blocks contents and online trackers that follow you around the web. Then there is the Screenshots feature with scrolling support that allows for a quick snap and share session.

Firefox can be customized according to the user’s preference by changing the search bar tool, themes, and default search engine from the settings.

⇒ Get Firefox

Google Chrome is the most popular web browser among Windows users. However, it is also known to collect user data when allowed, which is why it only landed the last position in our list.

Chrome also comes with all the standard security features such as automatic URL redirect from HTTP to HTTPS, VPN, and ad-blocker support through extensions and a familiar user interface across the devices.

The latest version of Google Chrome includes DuckDuckGo as a recommended search engine, making it a DuckDuckGo browser choice.

Note that there is even a DuckDuckGo extension for Chrome that you can use to shorten the process.

⇒ Get Google Chrome

All the browsers in this article allow you to change the default engine and set it to DuckDuckGo. Also, consider checking our list of browsers that don’t save your history and personal data.

With the constantly increasing rate of cyber security breaches, you may even consider using one of the best browsers without cookies to protect your online privacy.

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