GausianNB: Could not convert string to float: 'Thu Apr 16 23:58:58 2015'
To cast that column of your data-frame as type float try: 

k_train = train['cols_to_use'].astype(float)
target = train['final_status'].astype(float)


More documentation can be found here or you can cast them when loading the csv file sep=',' maybe usful assuming that your data is separated by a , in your CSV file

train = pd.read_csv("datasets/train2.csv", 
                    dtype={'cols_to_use': float , 'final_status': float})


Note that converting unix TimeStamp to readable date is very simple with the datetime library example:

import datetime 

datetime.datetime.fromtimestamp(1526972723).strftime('%Y-%m-%d %H:%M:%S')


I hope it's helpful.