There are 2 repositories under decision-tree-classifier topic.
A collection of research papers on decision, classification and regression trees with implementations.
Learning to create Machine Learning Algorithms
Implementation of basic ML algorithms from scratch in python...
A repository contains more than 12 common statistical machine learning algorithm implementations. 常见10余种机器学习算法原理与实现及视频讲解。@月来客栈 出品
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.
a chatbot based on sklearn where you can give a symptom and it will ask you questions and will tell you the details and give some advice.
Network Intrusion Detection based on various machine learning and deep learning algorithms using UNSW-NB15 Dataset
Projects I completed as a part of Great Learning's PGP - Artificial Intelligence and Machine Learning
Feature Selection using Metaheuristics Made Easy: Open Source MAFESE Library in Python
AI & Machine Learning: Detection and Classification of Network Traffic Anomalies based on IoT23 Dataset
Final Year Project on Road Accident Prediction using user's Location,weather conditions by applying machine Learning concepts.
This project detects whether a news is fake or not using machine learning.
Detect Fraudulent Credit Card transactions using different Machine Learning models and compare performances
Collection of various implementations and Codes in Machine Learning, Deep Learning and Computer Vision ✨💥
Decision Tree with PEP,MEP,EBP,CVP,REP,CCP,ECP pruning algorithms,all are implemented with Python(sklearn-decision-tree-prune included,All are finished).
Simple implementation of CART algorithm to train decision trees
Collection of Artificial Intelligence Algorithms implemented on various problems
Career Guidance System Using Machine Learning Techniques
Mousika: Enable General In-Network Intelligence in Programmable Switches by Knowledge Distillation (INFOCOM22 & ToN23)
Python implementation of Decision trees using ID3 algorithm
Myocardial Infarction Detection
Modular full-stack ML project leveraging Groq API, Streamlit, Supabase, JSON, SciPy, SciKit-Learn, Plotly & EmailJS, alongside libraries - NumPy, Pandas, Utils, OS, Base64, Re, Pillow & DateTime.
Abnormal Traffic Identification Classifier based on Machine Learning. My code for undergraduate graduation design.
c++ incremental decision tree
Determining the important factors that influences the customer or passenger satisfaction of an airlines using CRISP-DM methodology in Python and RapidMiner.
This is a binary classification problem related with Autistic Spectrum Disorder (ASD) screening in Adult individual. Given some attributes of a person, my model can predict whether the person would have a possibility to get ASD using different Supervised Learning Techniques and Multi-Layer Perceptron.
Predicting Political Ideology of Twitter Users.
:trident: Some recognized algorithms[Decision Tree, Adaboost, Perceptron, Clustering, Neural network etc. ] of machine learning and pattern recognition are implemented from scratch using python. Data sets are also included to test the algorithms.
#FakersGonnaFake: using simple statistical tools and machine learning to audit instagram accounts for authenticity
A system that is capable of automatically irrigating the agricultural field by sensing the parameters of soil in real-time and predicting crop based on those parameters using machine learning. The system also predicts the yield of the crop.
An implementation of the paper "A Short Introduction to Boosting"
The biggest module developed with complete focus on Feature Selection (FS) using Meta-Heuristic Algorithm / Nature-inspired evolutionary / Swarm-based computing.
Heart disease prediction using normal models and hybrid random forest linear model (HRFLM)
Speech_Emotion_detection-SVM,RF,DT,MLP
Predicting the default customers