Topic: "random-forest-classification"
ThomasJNicoletti/Pulsar
A Data Mining Streamlit Application for Astrophysical Prediction using Random Forest Classification in Python
Language: Python - Size: 23.4 MB - Last synced at: about 1 month ago - Pushed at: almost 5 years ago - Stars: 4 - Forks: 0

Sabaudian/Music_Genre_Classification_project
Audio Pattern Recognition project - Music Genres Classification
Language: Python - Size: 1.33 GB - Last synced at: about 2 months ago - Pushed at: 10 months ago - Stars: 2 - Forks: 0

PialGhosh2233/Liver_Cirrhosis_Prediction_using_Machine_Learning
Language: Jupyter Notebook - Size: 344 KB - Last synced at: about 2 months ago - Pushed at: 12 months ago - Stars: 2 - Forks: 1

ThomasJNicoletti/Driver
Driver Analysis with Factors and Forests: An Automated Data Science Tool using Python
Language: Python - Size: 55.7 KB - Last synced at: almost 2 years ago - Pushed at: about 3 years ago - Stars: 2 - Forks: 0

dshah98/Machine_Learning_with_R
Full machine learning practical with R.
Language: R - Size: 444 KB - Last synced at: over 1 year ago - Pushed at: almost 4 years ago - Stars: 2 - Forks: 1

debasishray16/StockPredictor
This project basically aims to provide a visual representation and comparative analysis of close price data related to different company ticker. It involves an interactive dashboard for users to display analysis and prediction of stocks data by using LSTM + XG-Boost model
Language: JavaScript - Size: 78.4 MB - Last synced at: 14 days ago - Pushed at: 3 months ago - Stars: 1 - Forks: 2

nitingour1203/credit-card-default-prediction
If you miss payments or you don't pay the right amount, your creditor may send you a default notice, also known as a notice of default. If the default is applied it'll be recorded in your credit file and can affect your credit rating. An account defaults when you break the terms of the credit agreement.
Language: Jupyter Notebook - Size: 2.82 MB - Last synced at: about 2 years ago - Pushed at: about 2 years ago - Stars: 1 - Forks: 0

dshah98/Machine_Learning_with_Python
Full machine learning practical with Python.
Language: Jupyter Notebook - Size: 210 MB - Last synced at: over 1 year ago - Pushed at: almost 4 years ago - Stars: 1 - Forks: 1

hafizcode02/product-clustering-classification-superstore
Product Segmentation (Clustering KMeans) & Classification (Random Forest & KNN) on Super Store Dataset
Language: Jupyter Notebook - Size: 0 Bytes - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0

amiegirl/Fellowship_AI
Sentiment Analysis of Movies Dataset
Language: Jupyter Notebook - Size: 417 KB - Last synced at: about 1 month ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

pronzzz/red-wine-quality
Machine Learning model to predict Red Wine Quality using Random Forest Classifier
Language: Jupyter Notebook - Size: 3.22 MB - Last synced at: 7 days ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

HanifaElahi/Machine-Learning
MACHINE LEARNING ALGORITHMS
Language: Jupyter Notebook - Size: 36.3 MB - Last synced at: almost 2 years ago - Pushed at: over 3 years ago - Stars: 0 - Forks: 1

arqchicago/rfc-heart
random forest classification (with hyperparameter tuning) on heart disease dataset.
Language: Python - Size: 1.02 MB - Last synced at: about 1 month ago - Pushed at: almost 4 years ago - Stars: 0 - Forks: 0

gonultasbu/random-forest-stump
Minimal implementation of Random Forest classifier using decision stumps and bootstrap sampling without sklearn.
Language: Python - Size: 15.6 KB - Last synced at: about 2 years ago - Pushed at: over 4 years ago - Stars: 0 - Forks: 0

kunjan-mhaske/Risky-loan-prediction-using-ML-in-R-Studio
Implemented and compared Random Forest, Decision Tree, KNN, SVM, and Logistic Regression outcomes with a confusion matrix. Concluded that Random Forest achieved the highest accuracy of 85% to predict the loan status for investors.
Language: HTML - Size: 2.32 MB - Last synced at: about 2 years ago - Pushed at: almost 5 years ago - Stars: 0 - Forks: 0

rubelbd82/Machine-Learning
Machine learning algorithms implemented in python. Some are implemented in R. Algorithms include XGBoost, Convolutional Neural Network, Recursive Neural Network, Support Vector Machine, K-nearest neighbors, Naive Bayes, Natural Language Processing
Language: Python - Size: 2.52 MB - Last synced at: about 2 years ago - Pushed at: over 5 years ago - Stars: 0 - Forks: 0
