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DTSTART;TZID=America/New_York:20210928T130000
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SUMMARY:Machine Learning Series by OARC—Random Forest Workshop
DESCRIPTION:Please register to attend this workshop at the bottom of this page. After filling out the registration form\, we will email you the Zoom link. \nAmarel account: You need an Amarel account to participate in the lab section Apply here as soon as possible. \nVPN setup: You have to be connected on Rutgers’ network or be on VPN to access Amarel resources. \nIf you have questions or need help\, please contact Janet Chang. \nTopics:\n1. Introduction to Machine Learning (ML) \n\nBig data and Machine Learning\nRelate Machine Learning to other disciplines\nMachine Learning algorithms\nClassification and Regression\n\n2. Understanding Random Forest (RF) \n\nApplications of Random Forests\nWhy Random Forests\nThe Random Forest Algorithm\nFundamental concepts – ML\, RF\n\n3. Implementing Random Forest \n\nFeature Importance and Feature Selection\nDealing with missing data\, and imbalanced data\nBest split of the node–node impurity\n\n\nOver-fitting and underfitting\nThe model performance\nThe model interpretability\n\n4. Lab Exercise \nWe will use cancer health data combined with gene expression data to build random forest models\, predicting output variables. Both classifier and regressor will be addressed. \nLab 1\, Set up\, and launch R \nLab 2\, Data preparation \n\n2a. pre-processing\,\n2b. data partition\,\n2c. missing data imputation\,\n2d. feature selection\n\nLab 3\, Building the RF model: \n\n3b. handling imbalanced data\n3c. building the RF model\n3d. turning the parameters\n\nLab 4\, Validation and model performance \n\n4a. prediction and Confusion Matrix — test data\n4b. ROC curve and AUC\n4c. k-fold cross-validation\n4d. parallel computing\n\nLab 5\, Visualization and the model interpretation \n\n5a. plotting the random forest tree\n5b. plotting feature importance\n5c. partial dependence plot (PDP)\n5d. MDS – multi-dimensional scaling plot of proximity matrix\n\n \nTo Register: \n\n	Notice: JavaScript is required for this content.
URL:https://oarc.rutgers.edu/event/machine-learning-series-by-oarc-random-forest-workshop-9-28-21/
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