Regression

10 easy steps to deploy an ML model with functions — Yesterday, DigitalOcean released their new serverless functions capability for public use along with some examples from their closed beta. I am writing this article to help you get started as you try out machine learning projects on this new computing approach. The new DigitalOcean functions work similarly to AWS lambda…

Table of contents : 1- Confusion Matrix (CM) 2- Multiclass Confusion Matrix (MCM) 3- Regression Confusion Matrix 4- RCM Accuracy AUC Score 5- RCM F1 AUC Score 6- Conclusion 1-Confusion Matrix (CM) Confusion matrix is a popular tool for summarizing the performance of a classification algorithm (A model which is used to predict a discrete variable) by…

I’ve seen quite a few blog posts out there on using categorical variables to color scatterplots, and a few more on adding regression lines to the plot to represent each group (a good example here). But what if you’d like to understand the broader relationship between x and y, despite…

Data. We have tons of it and each day we collect more and more. It sounds like a cool thing to own but without providing it any usage, data losses its value over time. One awesome way of uing data is by using it…

Large-scale Feature Selection of Risk Genetic Factors for Alzheimer’s Disease via Distributed Group Lasso Regression(arXiv) Author : Qingyang Li, Dajiang Zhu, Jie Zhang, Derrek Paul Hibar, Neda Jahanshad, Yalin Wang, Jieping Ye, Paul M. Thompson, Jie Wang Abstract : Genome-wide association studies (GWAS) have achieved great success in the genetic…

This article explains what a regression is from a statistical point of view and a machine learning vision. Regression problems are supervised learning problems (problems with labels used to train a model) characterized by two types of variables. …

In this study, I prepared a prediction model for car price prediction dataset with using scikit learn library linear regression model and coding the model in Python. For the feature selection part, Recursive feature selection ( RFE) and variance inflation factor(VIF) are used to fix multicollinearity problems of the model. …

How to compare regression models that have all or some variables in common — Often, the regression modeler is faced with a choice among two or more competing models for the same problem. …