I am trying to preprocess my dataset and needs some suggestion on it.
The training data shape is : (166573, 14)
The distribution of features :
As you can see, only the first 4 columns go to different max values. Rest of the columns have either 1 or 0 value (max: 1, min: 0)
**Null Handling: **
I have dropped claims_daysaway column as most of the values are NULL and replace tier's NaN values with its mean value.
Scaling features:
I have scaled features where max value varies and left others untouched.
X['scaled_distance']= sc.fit_transform(X['distance'].values.reshape(-1,1))
X['scaled_visit_count'] = sc.fit_transform(X['visit_count'].values.reshape(-1,1))
X['scaled_tier'] = sc.fit_transform(X['tier'].values.reshape(-1,1))
Is this right approach? or should I scale all features?