Скачать или смотреть Machine Learning in R - Supervised Learning

Here I show example of building Supervised Machine Learning for iris dataset. Supervised learning here presented use labeled datasets to train algorithms to classify data or predict outcomes accurately. The inputs (features is fed into 5 models). The models are: Linear Discriminant Analysis (lda), K-nearest neighbors’ algorithm (knn), Support Vector Machine (svm) using Radial function, Recursive Partitioning and Regression Trees (rpart) and Random Forest. Based on Accuracy (how well the model fit the data) and KAPPA (used to measure inter-rater reliability for qualitative (categorical) items). Prediction has been presented using validation dataset (remain 20% of all dataset). Confusion Matrix is presented with metrics that can allow us to evaluate the performance of the model that best fit the dataset.
Find this script here: https://github.com/josecome/data-scie...
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https://github.com/josecome
https://josecome.com

#datascience #dataanalysis #dataanalytics #r #datamining #machinelearning