There are 1 repository under decision-tree-algorithm topic.
I've demonstrated the working of the decision tree-based ID3 algorithm. Use an appropriate data set for building the decision tree and apply this knowledge to classify a new sample. All the steps have been explained in detail with graphics for better understanding.
C++ code for "A Faster Drop-in Implementation for Leaf-wise Exact Greedy Induction of Decision Tree Using Pre-sorted Deque"
Karma of Humans is AI
Quizzaro The Personality Quiz
MasterThesis on Congestion Detection in SDN networks using Machine Learning
A C++ project which efficiently solves any given N-puzzle using backtracking on a decision tree.
Implementation of Grid Search to find better hyper-parameters for decision tree to reduce the over fitting.
Machine Learning Software that predicts planets based on their distance from the sun, number of satellites and various properties
Decision Tree classifier from scratch without any machine learning libraries
Implementation of Decision Tree Algorithm using Python, Pandas, and NumPy without using any off the shelf library usi
QUEST is proposed by Loh and Shih (1997), and stands for Quick, Unbiased, Efficient, Statistical Tree. It is a tree-structured classification algorithm that yields a binary decision tree. A comparison study of QUEST and other algorithms was conducted by Lim et al (2000).
Prediction using Decision Tree Algorithm to create Decision Tree Classifier.
The code uses the scikit-learn machine learning library to train a decision tree on a small dataset of body metrics (height, width, and shoe size) labeled male or female. Then we can predict the gender of someone given a novel set of body metrics.
Distributed Decision Tree Induction using MPI
Naive Bayes and Decision Tree Classifiers implemented with Scikit-Learn and Graphviz visualization (Datasets - News, Mushroom, Income)
Analytical tool to help the company decide whether the employee will stay or not
Visualize a Decision Tree using dtreeviz
Projects based on Machine Leaning
Machine learning algorithms
A full-stack web application that syncs a user's FitBit data in order to generate workout suggestions
Machine Learning from Titanic Disaster
ID3 Decision Tree algorithm
Dive into Soulz, a strategic text-based adventure where combat prowess and exploration merge, guiding heroes through a perilous world teeming with challenges and evolving threats.
A simple classification problem where SVM, Logistic Regression, KNN and Decision Trees algorithms are used and the F1-score with Jaccard similarity scores are found out.
Create the Decision Tree classifier and visualize it graphically. The purpose is if we feed any new data to this classifier, it would be able to predict the right class accordingly.
Linear Discriminant Tree in jupyter notebook
This project is my under-graduation final year thesis project.
The goal of this project is to build a web application that will be trained on a set of labeled flower images to make predictions on the given input.
Decision Tree is a Supervised learning technique that can be used for both classification and Regression problems, but mostly it is preferred for solving Classification problems. It is a tree-structured classifier, where internal nodes represent the features of a dataset, branches represent the decision rules and each leaf node represents the outcome.
Various Machine learning algorithms
Problem to solve: Predict if a candidate would be hired based on specific characteristics; what are the most important features a candidate must have to have higher possibilities of getting the job?
For the THRILL of the hunt!
Implementation of various machine learning algorithms