All our Data Science projects include bite-sized activities to test your knowledge and practice in an environment with constant feedback.
All our activities include solutions with explanations on how they work and why we chose them.
Based on previous results, choice the correct answers.
Use the following code to compute the accuracy_score:
from sklearn.metrics import accuracy_score y_pred = tree.predict(X) accuracy_score(y_pred,y)
Round to two significant decimal
Select the correct answers using the information from the confusion matrix.
Separate the target and the features into two variables and create the response variable based on the columns Trump and Clinton.
Select the correct code to complete this task
There could be more than just one correct answer.
Initialize a Decision Tree classifier (name the model clf) and fit on the data with a random_state: 42 and max_depth : 3 (the maximum depth of our decision tree using the max_depth parameter).
Calculate the accuracy score of the training dataset. Select the correct answer.
Which of the following statements are True about classification?
Which of the following statements are examples of classification?
In which phase are model parameters adjusted?