A.I, Data and Software Engineering
Lasso, Ridge, and Elastic Net are excellent methods to improve the performance of your linear model. This post will summarise the usage of these regularization techniques. Bias: Biases are the underlying assumptions that are made by data to simplify the target function. Bias does help us generalize the data better and make the model less sensitive to single data points. It also decreases the...
The features you use influence more than everything else the result. No algorithm alone, to my knowledge, can supplement the information gain given by correct feature engineering.— Luca Massaron What is a feature and why we need engineering of it? Basically, all machine learning algorithms use some input data to create outputs. This input data comprise features, which are usually in the form...
A.I, Data and Software Engineering