Selected article for: "cross validation and training dataset"

Author: Sovesh Mahapatra; Prathul Nath; Manisha Chatterjee; Neeladrisingha Das; Deepjyoti Kalita; Partha Roy; Soumitra Satapathi
Title: Repurposing Therapeutics for COVID-19: Rapid Prediction of Commercially available drugs through Machine Learning and Docking
  • Document date: 2020_4_7
  • ID: m0q7rm6z_40
    Snippet: The training model is prepared by 80% of the original dataset. The dataset is completely classified from where the computer learns and finds the relations among various attributes. The cross-validation is used along with the algorithm to train the model. In this case, the cross-validation is n set with n-folds dataset. Then it is supposed to divide the training dataset into n parts, and the n-1 parts will be used as training data and the other on.....
    Document: The training model is prepared by 80% of the original dataset. The dataset is completely classified from where the computer learns and finds the relations among various attributes. The cross-validation is used along with the algorithm to train the model. In this case, the cross-validation is n set with n-folds dataset. Then it is supposed to divide the training dataset into n parts, and the n-1 parts will be used as training data and the other one will be used to validate the rest.

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