A curated list of gradient boosting research papers with implementations.
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Updated
Mar 16, 2024 - Python
A curated list of gradient boosting research papers with implementations.
Tree based algorithm in machine learning including both theory and codes. Topics including from decision tree regression and classification to random forest tree and classification. Grid Search is also included.
Solution for ENS - Societe Generale Challenge (1st place).
Customer Churn Analysis in R: Logistic, Classification Tree, XGBoost, Random Forest.
Gradient-based Entire Tree Optimization For Oblique Decision Tree
Building a binary classification model to determine whether or not an employee in the tech industry chooses to seek treatment for a mental health condition
R | Classification Project
Recursive Partitioning and Regression Trees adapted to Random Forests with more split functions
Exemplo de aprendizagem de máquina por K-ésimo Vizinho mais Próximo usando Python
Built and tested 6 supervised machine learning algorithm to develop a predictive classification model to classify 13000+ projects as success or failure.
KNN Algorithms, Naive Bayes, Classification Tree, PCA Implementations
Exploratory data analysis and classification tree algorithm (sklearn).
AutoValuate: A machine learning-driven tool for classifying used car prices as high or low, enabling smarter decisions in the car resale market.
This project is part of the Statistical Learning course.
evaluating credit default rate using statistical machine learning methods
Compilación de trabajos realizados en la asignatura de Machine Learning con Python
This University of Calgary DATA606 – Advanced Statistical Methods project examines a Portuguese bank’s telemarketing campaign, using statistical models to identify factors influencing term deposit subscriptions and provide recommendations to improve customer targeting and campaign effectiveness.
In this report, the goal is to predict Attrition by selecting a set of explanatory variables and building a random forest classification tree.
Machine learning model for: 1) sentiment analysis for online food reviews, 2) classify texts into topics, 3) predicting volcano eruption, 4) classify human genes
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