Functions to help in model building and evaluation
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Updated
Oct 12, 2018 - R
Functions to help in model building and evaluation
Classification ML Model to predict pre-owned cars purchase
An education company named X Education sells online courses to industry professionals. On any given day, many professionals who are interested in the courses land on their website and browse for courses.
Given project compares various machine learning classifiers and provides their results on car dataset of UCI Machine learning library.
A machine learning project in Python to predict the 2020 Australian Open Winner
Recognize underfitting and overfitting, implement bagging and boosting, and build a stacked ensemble model using a number of classifiers.
This Prediction is a research analysis process on data using classification algorithms to compare the accuracy rate for each algorithm given below on this Monkey Pox data such as ( K-Neighbors Classifier, RandomForest Classifier, AdaBoost Classifier, Bagging Classifier, Gradient Boosting Classifier, Decision Tree Classifier )
Model wine quality based on physiochemical tests - AI Fellowship Machine Learning Final Project
Machine learning agorithams
final project, classification base on tree data strucutures, random forest
This repository contains various classification, clustering and data analysis code.
Bagging with Naive Bayes, Machine Learning
Implementation of several ML models like decision tree, linear regression, ensemble methods, etc.
Python code using supervised learning to prioritize shelter animals by their probability of getting adopted to maximize the rate of adoption.
Exploratoy Data Analysis,Logistic Regression,Penalized Logistic Regression (LASSO), LDA, Decision Trees, Bagging, Random Forest
Vignette on bootstrapping and applications in machine learning.
Implementing random forest models in R with bagging and boosting.
Predict if the customer will churn or not
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