Various Classification models used are Logistic regression, K-NN, Support Vector Machine, Kernel SVM, Naive Bayes, Decision Tree Classification, Random Forest Classification using R
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Updated
Jan 18, 2018 - R
Various Classification models used are Logistic regression, K-NN, Support Vector Machine, Kernel SVM, Naive Bayes, Decision Tree Classification, Random Forest Classification using R
Implementation of k-Nearest Neighbours algorithm for use on geometric morphometric data and a simulated dataset.
One Data Set with multiple Algorithms
Data Science (Data preprocessing) along with machine learning where patients with digestive and kidney diseases are predicted using(kNN, Naïve Bayes , and Random Forest) classifiers in R Programming Language
Code for the project "Predicting hospital readmission of diabetic patients using ensemble learning"
Predicting whether the customer will subscribe to Term Deposits through Machine Learning Algorithms by R.
Project carried out on July 2020 for "Data Mining" (Higher Diploma in Data Analytics at National College of Ireland)
Basic R code to impute values into missing records, scrape data from the web and also to build and train k-nn classifier model.
KNN Classifier problem for classifying Glass type using the composition of elements
Practices and Assignments from the Fundamentals of Data Science Class
Classifying credit applicants with 9 different ML models
Vorhersage, ob ein Spender aufgrund seiner Vorgeschichte erneut Blut spenden wird. | Predicting whether a donor will return to donate blood given their donation history.
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