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Build logistic regression in Python from scratch easily

Implement Logistic Regression in Python from Scratch ! In this video, we will implement Logistic Regression in Python from Scratch. We will not use any build in models, but we will understand the code ...
IEEE

Evaluating Multi-K Bootstrap KNN Regression for Clustered Nonlinear Data

Abstract: This study evaluates the predictive accuracy, explanatory power, and interval estimation capabilities of the multi-K bootstrap K-nearest neighbor (KNN) regression method, specifically ...
IEEE

Multi-Output Regression for the Prediction of World-Class Performances in Women’s Handball

Abstract: The purpose of this study was to investigate the relationship between workload and in-game technical and athletic performance. To achieve this,A modeling approach that predicts multiple ...
Scientific Research Publishing

Zhang, S., Li, X., Zong, M., Zhu, X. and Cheng, D. (2017) Learning k for KNN Classification. ACM Transactions on Intelligent Systems and Technology, 8, 1-19.

ABSTRACT: This paper evaluates the performance of multiple machine learning models in predicting NBA game outcomes. Both regression and classification approaches were explored, with models including ...
Scientific Research Publishing

Guo, G., Wang, H., Bell, D., Bi, Y. and Greer, K. (2003) KNN Model-Based Approach in Classification. In: Meersman, R., Tari, Z. and Schmidt, D.C., Eds., Lecture Notes in ...

ABSTRACT: This paper evaluates the performance of multiple machine learning models in predicting NBA game outcomes. Both regression and classification approaches were explored, with models including ...
GitHub

Potentially serious regression in garbage collector performance in Python 3.14

[~/regression-testing]$ hyperfine --warmup=10 "cp313/python/bin/python3.13 dicttest.py" "cp314/python/bin/python3.14 dicttest.py" Benchmark 1: cp313/python/bin ...
Frontiers

Predicting millennial farmer success by highlighting the role of digitalization and technology in increasing productivity

This study aims to analyze the main factors that affect the success of millennial farmers in increasing quantity in Indonesia. This study uses a quantitative approach with the K-Nearest Neighbors ...
SciELO

Obesity classification: a comparative study of machine learning models excluding weight and height data

OBJECTIVE: Obesity is a global health problem. The aim is to analyze the effectiveness of machine learning models in predicting obesity classes and to determine which model performs best in obesity ...