How to convert feature names (column names), resulted by tsfresh extract_features, to format, compatible with ComprehensiveFCParameters.
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To save and parse selected features in
tsfresh, you can follow these steps:Saving Selected Features:
1.Extract Features: Use
tsfresh.extract_featuresto extract a large set of features from your time series data.2.Select Features: Identify and select the features you want to save based on your requirements.
3.Save Selected Features: Save the selected features to a file (e.g., CSV) for future use.
Parsing Selected Features:
1.Load Selected Features: Load the previously saved selected features from the file.
2.Use Selected Features: Use the selected features as needed for further analysis or modeling.
Notes:
'feature1','feature2', etc.) match exactly with the names in your extracted features DataFrame.pd.read_csvin this example) based on the format you choose for saving the selected features.To save and parse selected features in `tsfresh`:
# Saving Selected Features
1. Extract Features:
“`python
from tsfresh import extract_features
extracted_features = extract_features(data, column_id=’id’, column_sort=’time’)
“`
2. Select Relevant Features:
“`python
from tsfresh import select_features
from tsfresh.utilities.dataframe_functions import impute
impute(extracted_features)
selected_features = select_features(extracted_features, y)
“`
3. Save Selected Features:
“`python
selected_features.to_csv(‘selected_features.csv’)
“`
# Parsing and Converting Feature Names
1. Load Selected Features:
“`python
import pandas as pd
selected_features = pd.read_csv(‘selected_features.csv’, index_col=0)
“`
2. Convert to Compatible Format:
“`python
from tsfresh.feature_extraction import ComprehensiveFCParameters
import re
def convert_feature_names(selected_features):
new_params = {}
for feature in selected_features.columns:
match = re.match(r'(.+?)__([^_]+)_(.+)’, feature)
if match:
feature_name, param, value = match.groups()
if feature_name not in new_params:
new_params[feature_name] = {param: [value]}
else:
new_params[feature_name].setdefault(param, []).append(value)
return new_params
compatible_format = convert_feature_names(selected_features)
Explanation
– Extract Features: Initial feature extraction.
– Select Features: Choose relevant features.
– Save to CSV: Save for future use.
– Convert Names: Format for `ComprehensiveFCParameters`.
This prepares features for further analysis or model training.