Predicting Horse Survival with Colic using Logistic Regression

A dataset for predicting survival in horses with colic contains 368 samples and 28 features. Colic refers to abdominal pain, which may stem from gastrointestinal or other issues. The dataset includes hospital measurements, some of which are subjective or difficult to quantify, such as pain level. Additionally, approximately 30% of the values ar ...

Posted on Thu, 08 Oct 2026 16:26:32 +0000 by magic-chef

Implementing Binary Classification with Logistic Regression in Python

Binary Classification OverviewLogistic regression serves as a foundational algorithm for binary classification tasks where the target variable consists of two distinct categories. Typical scenarios include spam detection, medical disease screening, and customer churn prediction.The algorithm transforms linear regression outputs into probabiliti ...

Posted on Thu, 18 Jun 2026 17:09:32 +0000 by jaylearning

Logistic Regression Explained with Code

Logistic Function Logistic regression is a generalized linear model, sharing many similarities with multiple linear regression. We define the logistic function (sigmoid) as: $$ g(z) = \frac{1}{1 + e^{-z}} $$ With $ z = \theta^T x $, the hypothesis becomes: $$ h_\theta(x) = \frac{1}{1 + e^{-\theta^T x}} $$ The graph of the logistic function is: ...

Posted on Sun, 07 Jun 2026 17:49:35 +0000 by bals28mjk

Implementing and Evaluating Eight Machine Learning Algorithms on the Iris Dataset with 5-Fold Cross-Validation

This document details the implementation and evaluation of eight machine learning algorithms on the classic Iris dataset using 5-fold cross-validation. The algorithms include: Logistic Regression, C4.5 Decision Tree (with pre- and post-pruning), SMO-based SVM, BP Neural Network, Naive Bayes, K-means Clustering, and Random Forest. Experiment 1: ...

Posted on Thu, 07 May 2026 09:29:13 +0000 by robs99