tree-pruning

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SamRagusa /Batch-First

A JIT compiled chess engine which traverses the search tree in batches in a best-first manner, allowing for neural network batching, asynchronous GPU use, and vectorized CPU computations.

chess neural-network tensorflow gpu engine numpy llvm jit artificial-intelligence batch convolutional-neural-networks tree-search ann numba jit-compiler chess-ai inception-module tree-pruning negamax-algorithm k-best-first

UpdatedMar 12, 2022
Python

abhinav-bohra /DecisionTrees

Star6

Implementation of Decision Tree Algorithm using Python, Pandas, and NumPy without using any off the shelf library usi

numpy pandas decision-tree-algorithm id3-algorithm tree-pruning decisiontrees shelf-library-usi

UpdatedJan 27, 2023
Jupyter Notebook

yashjshah /Employee-Data-Analysis

Star3

Analytical tool to help the company decide whether the employee will stay or not

r analytics analysis svm decision-making prediction predictive logistic-regression decision-trees predictive-modeling boruta predictive-analytics hypothesis-testing decision-tree decision-tree-classifier decision-tree-algorithm aic decision-tree-regression tree-pruning auc-roc-curve

UpdatedFeb 14, 2019
R

eric9n /clade

Star1

A tool for phlyo tree, a phylogenetic tree construction software.

phylogenetics phylogenetic-tree tree-pruning gtdb

UpdatedSep 9, 2024
Rust

marufgreat /decision_tree_paper_vietnam

Star1

Research Paper for The International Conference on Intelligent Systems and Data Science (ISDS 2023), College of Information and Communication Technology (CICT), Can Tho University (CTU), Can Tho, Vietnam

decision-tree-classifier classification-algorithm tree-pruning

UpdatedJul 13, 2023
Jupyter Notebook

anarmawala /chess-ai

Star1

Chess AI written in Rust that uses the min/max algorithm and tree pruning so predict 5-6 moves ahead.

game algorithm chess ai tree-pruning min-max-optimization

UpdatedAug 23, 2020
Rust

kaushikmanikonda /Industrial-Data-Analytics-and-Machine-Learning_ISEN_613

Star0

Data Analytics and Machine Learning in R. Linear-regression, Logistic-regression, Hierarchical-clustering, Boosting, Bagging, Random-forests, K-means-clustering, K-nearest-neighbors (K-N-N), Tree-pruning, Subset-selection, LDA, QDA, Support Vector Machines (SVM)