random forest classification (with hyperparameter tuning) on heart disease dataset.
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Updated
May 25, 2021 - Python
random forest classification (with hyperparameter tuning) on heart disease dataset.
Sentiment Analysis of Movies Dataset
Machine Learning model to predict Red Wine Quality using Random Forest Classifier
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
Predicted the disease using the symptoms observed in the patients.
Driver Analysis with Factors and Forests: An Automated Data Science Tool using Python
In this project the data is been used from UCI Machinery Repository. Main aim of this project is to predict telling tumor of each patient is Benign (class – 2) or Malignant (class – 4) the models used are – Decision tree Classification, Logistic Regression, K-Nearest Neighbors, SVM, Kernel SVM, Naïve-Bayes and Random Forest Classification.
Random forests is a supervised learning algorithm. It can be used both for classification and regression. It is also the most flexible and easy to use algorithm. A forest is comprised of trees. It is said that the more trees it has, the more robust a forest is. Random forests creates decision trees on randomly selected data samples, gets predict…
Data analysis project on Digital Addiction for master thesis
Prediction of students' dropout using classification models. Data visualisation, feature selection, dimensionality reduction, model selection and interpretation, parameters tuning.
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.
A Data Mining Streamlit Application for Astrophysical Prediction using Random Forest Classification in Python
This repository will help in understanding the basic concept of Random Forest algorithm and will also learn how to optimize the hyperparameters and prevent overfitting.
Build and evaluate classification model using PySpark 3.0.1 library.
Minimal implementation of Random Forest classifier using decision stumps and bootstrap sampling without sklearn.
Audio Pattern Recognition project - Music Genres Classification
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.
MACHINE LEARNING ALGORITHMS
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