What is the best way to decide how many epochs of training to perform? It is always obvious looking at the decision boundary when the model begins to overfit. None of the others. As soon as the value of the Testing dataset performance begins to decrease. the valuIe of the Tuning datacot no hoginc
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- If you have a training set with millions of features, which Linear Regression training procedure should you use?Model evaluation Create a predictions variable using your fitted model and the test dataset; call it y_pred. Then get the accuracy score of your predictions and save it in a variable called accuracy. Finally get the confusion matrix for your predictions and save it in a variable called confusion_mat. Code: y_pred = Noneaccuracy = Noneconfusion_mat = NoneAn established strategy is useful. Give instances of different testing techniques.
- What exactly is the point of separating the data into a training set and a testing set? It is not obvious what the goal of the training set is. What exactly is the validation set supposed to accomplish?A group of researchers conducted a study to investigate the effectiveness of a new teaching method for a particular subject. They randomly assigned 100 students to two groups: one group received the new teaching method, and the other group received the traditional teaching method. At the end of the semester, they measured the students' performance on a standardized test. The researchers found that the mean score for the group that received the new teaching method was higher than the mean score for the group that received the traditional teaching method. How can the researchers test the hypothesis that the new teaching method is more effective than the traditional teaching method? What statistical test should they use?The hyper-parameters of a model must NOT be tuned on the test data ( i.e, the data used to evaluate the performance of the final model after selecting the hyper-parameters) Group of answer choices True False
- Do an analysis of a real data set and also mention where did you find the data set. Please do analysis completely in R studio. A basic requirement for the data set is that it includes one response variable and at least two predictor variables.The main objectives of this question are• to identify a suitable data set,• to come up with meaningful research questions based on the data,• to experience some of the problems encountered when analyzing real data,Also mention:• Where I find the data set?• Why the problem is of interest?• Which method or model is appropriate to this problem?• How do I apply the method to analysis the data set?• What is my conclusion?We have high-bias unregularized weak classifier that classifies each point correctly with training accuracy of 52%. How do you suggest to improve its performance? Discuss all possible approaches.The only way to tell if a model is right or wrong is to see how well it works on test data. tell me more; give me more information? Explain?