We can start with this. This heatmap shows the correlations, both direct and inverse, between all our different variables. We…

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## Small questions about “bigger” issues in Machine learning

“Statistical modeling: Two Cultures”, highlights an important distinction between two very different approaches to statistical modeling:Stochastic techniques, where a distribution…

Continue Reading## Classification: A Linear Approach (Part 1)

We know by looking at the dataset plot that this is exactly the region where most of our Orange class…

Continue Reading## How to read a Regression Table

How to read a Regression TableSharad VijalapuramBlockedUnblockFollowFollowingMar 31Photo by Isaac Smith on UnsplashWhat is regression?Regression is one of the most important…

Continue Reading## Comprehensive Guide To Logistic Regression In R

Comprehensive Guide To Logistic Regression In RSahiti KappagantulaBlockedUnblockFollowFollowingJan 28Logistic Regression in R -EdurekaThe evolution of Machine Learning has changed the entire 21st…

Continue Reading## Linear regression and a quality bottle of wine

Read on to find out. Akhilesh RaiBlockedUnblockFollowFollowingApr 11There is something about statistics that govern our lives more than we think. The…

Continue Reading## Using machine learning to predict Kickstarter success

How can you optimise for success?Laura LewisBlockedUnblockFollowFollowingApr 9Project aimsIn recent years, the range of funding options for projects created by individuals…

Continue Reading## A Comparison of Shrinkage and Selection Methods for Linear Regression

Run cross-validation trying a set of different values and pick one that minimizes cross-validated error on test data. Luckily, Python’s…

Continue Reading## The Complete Beginner’s Guide to Machine Learning: Multiple Linear Regression in 4 Lines of Code!

Multiple linear regression (MLR/multiple regression) is a statistical technique. It can use several variables to predict the outcome of a…

Continue Reading## Data Science Interview: Linear Regression Explained

Data Science Interview: Linear Regression ExplainedLinear regression explained in a non-technical wayJoy Gracia HarjantoBlockedUnblockFollowFollowingApr 5Data science is an emerging field…

Continue Reading## The Fundamental Algorithms of Data Science

And how do we find it?Cost functionIn the univariate case, each predicted value of y (denoted as y with a…

Continue Reading## Comprehensive Guide To Linear Regression In R

Comprehensive Guide To Linear Regression In RSahiti KappagantulaBlockedUnblockFollowFollowingJan 28Linear Regression — EdurekaLinear Regression is one of the most widely used Machine Learning algorithms,…

Continue Reading## The complete beginner’s guide to machine learning: simple linear regression in four lines of code!

In order to figure that out, we’ll create a model that will tell us what is the best fitting line…

Continue Reading## Statistical Overview of Linear Regression (Examples in Python)

Statistical Overview of Linear Regression (Examples in Python)Jovan MedfordBlockedUnblockFollowFollowingMar 23In statistics we are often looking for ways to quantify relationships between…

Continue Reading## Tree-Based Methods: Classification

Tree-Based Methods: ClassificationKushal ValaBlockedUnblockFollowFollowingMar 22The article is based on the Classification task by Decision Tree Algorithm, which is used more…

Continue Reading## How Does Linear Regression Actually Work?

How Does Linear Regression Actually Work?Anas Al-MasriBlockedUnblockFollowFollowingMar 18(Source: https://www. sciencenews. org/article/online-reading-behavior-predicts-stock-movements)Linear Regression is inarguably one of the most famous topics in…

Continue Reading## Logistic Regression as a Nonlinear Classifier

Most certainly not. As p goes from 0 to 1, log(p/(1-p)) goes from -inf to +inf. So we need f…

Continue Reading## Imbalanced Class Sizes and Classification Models: A Cautionary Tale

', 'Classes in rebalanced test set with ADASYN:',dict(zip(yvals_ads, counts_ads)))y_pred_smt = fit_logistic_regression_classifier(X_smoted, y_smoted)plot_confusion_matrix(ytest, y_pred_smt)y_pred_ads = fit_logistic_regression_classifier(X_adasyn, y_adasyn)plot_confusion_matrix(ytest, y_pred_ads)3. Gridsearch on balanced…

Continue Reading## Churn Prediction and Prevention in Python

And how would you know what to focus on if you wanted to keep them and how much you could…

Continue Reading## Machine Learning Algorithms In Layman’s Terms, Part 1

You could probably do it manually, but it would take forever. That’s where gradient descent comes in!Our “line of best…

Continue Reading## Data Structure Evaluation to Choose the Optimal Machine Learning Method

Data Structure Evaluation to Choose the Optimal Machine Learning MethodA set of examples on how analysis of data interdependencies helps save…

Continue Reading## A beginner’s guide to Linear Regression in Python with Scikit-Learn

A beginner’s guide to Linear Regression in Python with Scikit-LearnNagesh Singh ChauhanBlockedUnblockFollowFollowingFeb 25sourceThere are two types of supervised machine learning…

Continue Reading## Simulating(Replicating) R regression plot in Python using sklearn

Simulating(Replicating) R regression plot in Python using sklearnvikashraj luhaniwalBlockedUnblockFollowFollowingFeb 22When it comes to data science and machine learning workloads, R and…

Continue Reading## Regression, modular arithmetic, and PQC

Linear regressionSuppose you have a linear regression with a couple predictors and no intercept term:β1×1 + β2×2 = y +…

Continue Reading## Gradient Descent for Machine Learning

We can use the same equation in order to represent the regression line in computer. If you can’t recall it,…

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