How to do recursive feature elimination in Python?

How to do recursive feature elimination in Python?

How to do recursive feature elimination in Python?

This recipe helps you do recursive feature elimination in Python


Recipe Objective

To increse the score of the model we need to remove the features which are recursive. Removing recursive feature reduces the computational cost and increase the efficiency.

So this is the recipe on How we can do recursive feature elimination in Python.

Step 1 - Import the library

from sklearn.datasets import make_regression from sklearn.feature_selection import RFECV from sklearn import linear_model

We have only imported datasets to import the datasets, RFECV and liner_model.

Step 2 - Setting up the Data

We have imported inbuilt boston dataset and stored data in X and target in y. We have also used print statement to print rows of the dataset. dataset = datasets.load_boston() X = y =

Step 3 - Selecting recursive Features

We have used linear Regression as a model and RFECV is used for recursive feature elimination we have used negative mean squared error as a scoring with cross validation as 4. We have fit and transform rfecv. ols = linear_model.LinearRegression() rfecv = RFECV(estimator=ols, step=1, scoring="neg_mean_squared_error", cv=4, verbose=0, n_jobs=4), y) rfecv.transform(X) print(rfecv) print(rfecv.n_features_) So the output comes as

   estimator=LinearRegression(copy_X=True, fit_intercept=True, n_jobs=None,
   min_features_to_select=1, n_jobs=4, scoring="neg_mean_squared_error",
   step=1, verbose=0)


Relevant Projects

Resume parsing with Machine learning - NLP with Python OCR and Spacy
In this machine learning resume parser example we use the popular Spacy NLP python library for OCR and text classification.

Perform Time series modelling using Facebook Prophet
In this project, we are going to talk about Time Series Forecasting to predict the electricity requirement for a particular house using Prophet.

Natural language processing Chatbot application using NLTK for text classification
In this NLP AI application, we build the core conversational engine for a chatbot. We use the popular NLTK text classification library to achieve this.

Predict Churn for a Telecom company using Logistic Regression
Machine Learning Project in R- Predict the customer churn of telecom sector and find out the key drivers that lead to churn. Learn how the logistic regression model using R can be used to identify the customer churn in telecom dataset.

Human Activity Recognition Using Smartphones Data Set
In this deep learning project, you will build a classification system where to precisely identify human fitness activities.

Walmart Sales Forecasting Data Science Project
Data Science Project in R-Predict the sales for each department using historical markdown data from the Walmart dataset containing data of 45 Walmart stores.

Data Science Project - Instacart Market Basket Analysis
Data Science Project - Build a recommendation engine which will predict the products to be purchased by an Instacart consumer again.

Data Science Project-TalkingData AdTracking Fraud Detection
Machine Learning Project in R-Detect fraudulent click traffic for mobile app ads using R data science programming language.

Build an Image Classifier for Plant Species Identification
In this machine learning project, we will use binary leaf images and extracted features, including shape, margin, and texture to accurately identify plant species using different benchmark classification techniques.

Credit Card Fraud Detection as a Classification Problem
In this data science project, we will predict the credit card fraud in the transactional dataset using some of the predictive models.