I have one dataset of "Books" which contains 8 columns initially and out of which 3 of them contains text values which can be categorized. The 3 columns contains "Language-code", "Author Name" and "title" of the book. As sklearn LinearRegression don't take text as input so i decided to categorize these 3 columns by using "pandas_getdummies(...)" but after categorizing it the columns number exceeded to 20072 from 8 which is way too high.
So my queries are:
- What to do with the title name? Categorizing it doesn't seems right.
- What to with the rest 2 columns? If i leave the title name then the number of columns exceeds to 7646. Is there any other algorithm where i can directly feed the dataset without categorization?
- How to handle these large number of features after categorizing?