Predicting Win/Loss/Draw on the Connect Four dataset with Tsetlin Machines
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Updated
Dec 20, 2019 - Python
Predicting Win/Loss/Draw on the Connect Four dataset with Tsetlin Machines
using Multi-Layer Perceptron (MLP) to analyze its different settings on the Iris and Glass identification datasets
Master's Thesis project at University of Agder, Spring 2020. Classification with Tsetlin Machine on board game 'GO'.
Implementing Linear Regression for various degrees and computing RMSE with k fold cross validation, all from scratch in python.
This is software for the 10-fold validation of an CNN-based image-classification method.
Creating and visualising statistics from the results of k-fold validation.
This toolbox offers 7 machine learning methods for regression problems.
This toolbox offers 6 machine learning methods including KNN, SVM, LDA, DT, and etc., which are simpler and easy to implement.
Classification of mushrooms using decision tree in ID3 implementation
Using the dataset compiled by Dean De Cock. Applying Feature Transformation, Feature Selection and K-fold Cross Validation
Personal Project 2: using machine learning algorithms to predict the existence of heart disease based on a numerical and categorical dataset.
Implemented Linear Regression Algorithm from scratch to predict species in Iris data using k-fold cross validation
POS Tagger
MLB Team Runs Allowed Prediction Project (Linear Regression)
my machine learning practices for my third year in MFCI CS department
K fold cross validation for Tensorflow datasets
A thesis submitted in partial fulfilment of the award of the degree of MSc Computer Science (Software Engineering) from Staffordshire University
Pada project ini, akan dilakukan identifikasi nilai mata uang rupiah dengan menggabungkan metode ekstrasi ciri Local Binary Pattern dan metode klasifikasi Naïve Bayes. Serta untuk pengukuran akurasi identifikasi dilakukan dengan metode evaluasi K-Fold Cross Validation. Dataset yang digunakan berupa citra dengan rincian terdapat 120 citra yang te…
Detecting Laryngeal Cancer from CT SCAN images using Improvised Deep Learning based Mask R-CNN Model
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