Supervised Learning - English
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- Machine Learning using R - old 2022 Tutorials - English
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Supervised Learning -
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Unsupervised Learning -
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Data Cleaning using R -
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Linear Discriminant Analysis in R -
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Quadratic Discriminant Analysis in R -
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Support Vector Machine using R -
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Logistic Regression using R -
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K-Means Clustering in R -
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Hierarchical Clustering in R -
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Decision Tree using R -
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Random Forest using R
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Outline:
Supervised Learning About Machine Learning and its types. About iris species and its measurement parameters. Load the iris dataset and libraries. How to pose a Machine Learning problem? About supervised learning and its types. About Naive Bayes classifier. Use the test set to evaluate the performance of the model. Train a classification model with a Naive Bayes classifier. Confusion matrix and its use. Check the accuracy using True positive and True negative values.
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| Duration: | 00:13:11 | Size: | 6.1 MB |
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Introduction to basics of R
