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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...
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 repository contains more than 12 common statistical machine learning algorithm implementations. 常见机器学习算法原理与实现
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.
Projects I completed as a part of Great Learning's PGP - Artificial Intelligence and Machine Learning
Network Intrusion Detection based on various machine learning and deep learning algorithms using UNSW-NB15 Dataset
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).
Final Year Project on Road Accident Prediction using user's Location,weather conditions by applying machine Learning concepts.
Detect Fraudulent Credit Card transactions using different Machine Learning models and compare performances
AI & Machine Learning: Detection and Classification of Network Traffic Anomalies based on IoT23 Dataset
Collection of Artificial Intelligence Algorithms implemented on various problems
Simple implementation of CART algorithm to train decision trees
Python implementation of Decision trees using ID3 algorithm
Career Guidance System Using Machine Learning Techniques
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 project detects whether a news is fake or not using machine learning.
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
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.
An implementation of the paper "A Short Introduction to Boosting"
Speech_Emotion_detection-SVM,RF,DT,MLP
Myocardial Infarction Detection
Predicting the default customers
Build serialisable flowchart-style decision trees with D3.
IDS Alert Prioritization INSuRE Research Project
Heart disease prediction using normal models and hybrid random forest linear model (HRFLM)