Feature Selection Techniques

010420201017 Forward selection is an iterative method in which we start with no function in the model. In each iteration, we add a function that […]

300320202100 RFECV differs from Recursive Feature Elimination (RFE) in the function selection process in that it indicates the OPTIMAL NUMBER OF VARIABLES and not the […]

300320202027 Embedded methods are iterative in a sense that takes care of each iteration of the model training process and carefully extract those features which […]

300320201719 It is a greedy optimization algorithm which aims to find the best performing feature subset. It repeatedly creates models and keeps aside the best […]

300320201313 In backward elimination, we start with all the features and removes the least significant feature at each iteration which improves the performance of the […]

300320201248 Forward selection is an iterative method in which we start with no function in the model. In each iteration, we add a function that […]

290320202006 Collinearity is the state where two variables are highly correlated and contain similar information about the variance within a given dataset. The Variance Inflation […]

290320201454 In [1]: import numpy as np import pandas as pd import seaborn as sns import matplotlib.pyplot as plt from sklearn.preprocessing import LabelEncoder, OneHotEncoder import warnings […]

280320200940 Source of data: https://archive.ics.uci.edu/ml/datasets/Air+Quality In this case, statistical methods are used: We always have continuous and discrete variables in the data set. This procedure […]

categorical input – categorical output 260320201223 In this case, statistical methods are used: We always have continuous and discrete variables in the data set. This […]