Keras is a deep learning library that wraps the efficient numerical libraries Theano and TensorFlow. In this post, you will discover how to develop and evaluate neural network models using Keras for a regression problem. After completing this step-by-step tutorial, you will know: How to load a CSV dataset and make it available to Keras […]

# Search results for "regression"

## Spot-Check Regression Machine Learning Algorithms in Python with scikit-learn

Spot-checking is a way of discovering which algorithms perform well on your machine learning problem. You cannot know which algorithms are best suited to your problem before hand. You must trial a number of methods and focus attention on those that prove themselves the most promising. In this post you will discover 6 machine learning […]

## Classification And Regression Trees for Machine Learning

Decision Trees are an important type of algorithm for predictive modeling machine learning. The classical decision tree algorithms have been around for decades and modern variations like random forest are among the most powerful techniques available. In this post you will discover the humble decision tree algorithm known by it’s more modern name CART which stands […]

## Logistic Regression Tutorial for Machine Learning

Logistic regression is one of the most popular machine learning algorithms for binary classification. This is because it is a simple algorithm that performs very well on a wide range of problems. In this post you are going to discover the logistic regression algorithm for binary classification, step-by-step. After reading this post you will know: […]

## Logistic Regression for Machine Learning

Logistic regression is another technique borrowed by machine learning from the field of statistics. It is the go-to method for binary classification problems (problems with two class values). In this post you will discover the logistic regression algorithm for machine learning. After reading this post you will know: The many names and terms used when […]

## Linear Regression Tutorial Using Gradient Descent for Machine Learning

Stochastic Gradient Descent is an important and widely used algorithm in machine learning. In this post you will discover how to use Stochastic Gradient Descent to learn the coefficients for a simple linear regression model by minimizing the error on a training dataset. After reading this post you will know: The form of the Simple […]

## Simple Linear Regression Tutorial for Machine Learning

Linear regression is a very simple method but has proven to be very useful for a large number of situations. In this post, you will discover exactly how linear regression works step-by-step. After reading this post you will know: How to calculate a simple linear regression step-by-step. How to perform all of the calculations using […]

## Linear Regression for Machine Learning

Linear regression is perhaps one of the most well known and well understood algorithms in statistics and machine learning. In this post you will discover the linear regression algorithm, how it works and how you can best use it in on your machine learning projects. In this post you will learn: Why linear regression belongs […]

## Non-Linear Regression in R with Decision Trees

In this post, you will discover 8 recipes for non-linear regression with decision trees in R. Each example in this post uses the longley dataset provided in the datasets package that comes with R. The longley dataset describes 7 economic variables observed from 1947 to 1962 used to predict the number of people employed yearly. Let’s get started. Classification […]

## Non-Linear Regression in R

In this post you will discover 4 recipes for non-linear regression in R. There are many advanced methods you can use for non-linear regression, and these recipes are but a sample of the methods you could use. Let’s get started. Each example in this post uses the longley dataset provided in the datasets package that comes with R. The […]