Tag: scikit-learn

Total 28 Posts

Kernel Density Estimation in Python Using Scikit-Learn

Introduction

This article is an introduction to kernel density estimation using Python's machine learning library scikit-learn.

Kernel density estimation (KDE) is a non-parametric method for estimating the probability density function of a given random variable. It is also referred to by its traditional name, the Parzen-Rosenblatt Window method, after its

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Ensemble/Voting Classification in Python with Scikit-Learn

Introduction

Ensemble classification models can be powerful machine learning tools capable of achieving excellent performance and generalizing well to new, unseen datasets.

The value of an ensemble classifier is that, in joining together the predictions of multiple classifiers, it can correct for errors made by any individual classifier, leading to

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Gradient Boosting Classifiers in Python with Scikit-Learn

Introduction

Gradient boosting classifiers are a group of machine learning algorithms that combine many weak learning models together to create a strong predictive model. Decision trees are usually used when doing gradient boosting. Gradient boosting models are becoming popular because of their effectiveness at classifying complex datasets, and have recently

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Predicting Customer Ad Clicks via Machine Learning

Introduction

Internet marketing has taken over traditional marketing strategies in the recent past. Companies prefer to advertise their products on websites and social media platforms. However, targeting the right audience is still a challenge in online marketing. Spending millions to display the advertisement to the audience that is not likely

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