What type of Naïve Bayes model uses a binary data type?  

Which of the following is the correct way to implement One Hot Encoding for a data frame  called “df” and the OneHotEncoder() is assigned to “ohe” as instance?  

Some common questions that have been asked:1.     you MUST take the test on a web camera enabled computer—mobile phones are not permitted to be used to take the test or during the test.2.     You must have a dedicated WiFi connection—hotspots cannot be used as they do not provide a strong connection. 3.     You MUST CLOSE all tabs that are open except the exam tab; otherwise, the exam will not open and you will be asked to force its closing. No extra monitors, tablets, laptops or outside assistance is permitted.4.     You must have an ID to begin the exam. A student ID or driver’s license is acceptable.Students will have ONE opportunity to complete this closed note/book timed exam. Once the exam has been opened, it MUST be completed.If you are encountering software/access errors, you need to contact Honor Lock or the CCAC helpdesk—not the professor.

A rising inflation rate is good news for which of the following groups?

Financial plans should include objectives and goals in each of the following areas EXCEPT _______.

What purposed does the following function have?      %matplotlib inline  

Which of the following is the correct syntax to print all rows and first three columns of data frame “data” with 50 rows and 50 columns?

Write a function rmse that takes in truth and prediction values and returns the root-mean-squared error. Use sklearn’s ‘mean squared error’ class. All variables are as per assignment   A. from sklearn.metrics import mean_squared_error def rmse(ytrue):     return np.sqrt(mean_squared_error(ytrue, ypredicted))   B. from sklearn.metrics import mean_squared_error def rmse(ytrue, ypredicted):     return np.sqrt(mean_squared_error(ypredicted))   C. from sklearn.metrics import mean_squared_error def rmse(ytrue, ypredicted):     return np.sqrt(mean_squared_error(ytrue, ypredicted))   D. from sklearn.metrics import mean_squared_error def rmse(ypredicted):     return np.sqrt(mean_squared_error(ytrue, ypredicted))

Which Pandas one-hot encoder method works well with data that is defined as categorical? All variables are as per assignment A.      data = pd.get_dummies(data, columns=one_hot_encode_cols) B.      data = pd.get_var(data, columns=one_hot_encode_cols) C.       data = pd.get_ohc(data, columns=one_hot_encode_cols) D.       data = pd.get_cols(data, columns=one_hot_encode_cols)

How would you reset the index of a dataframe with a new index given as list? The new index is given by ” new_index” and “df” is a pandas dataframe