Which of the following is a method for handling categorical variables in a supervised learning model?Review LaterOne-hot encodingLabel encodingbinary encodingall the above

15. A data analyst wants to train a machine learning model. While conducting exploratory data analysis, the analyst noticed that there is a categorical column in the data called `size`, which contains the categories "big," "medium," and "small." The analyst wants to encode these categories into numerical values to avoid errors when training the machine learning model. The analyst is unsure which encoding method to use for this variable and has reached out to you for help. Which of the following encoding methods would you suggest as the most appropriate in this situation?Count Frequency encodingOrdinal encodingOne Hot EncodingNone of the above

Which of the following is a valid method for handling categorical data in ML?*1 pointo A) One-hot encodingo B) Mean normalizationo C) Log transformationo D) Principal Component Analysis

Based on the above identified features, encode the categorical values. Fill in the neccessary dictionaries below.

Which is NOT a typical step in preparing data for training a decision tree?Review LaterOne-hot encoding categorical variablesNormalizing featuresHandling missing valuesConverting target variable into categorical format

In preparing categorical variables for analysis, it is usually best to ...Group of answer choicesconvert the categories to binary, dummy variables.convert the categories to string values.let them remain categorical.omit all categorical variables.