The way energy is being wasted, soon light bills might be the scariest thing for a lot of us. Not an extreme but a simple temporary solution can be switching to better lights. So, this challenge brings you attributes and asks you to predict the
class of the LED bulb.
The database contains various attributes about LED lights which are used almost everywhere. The database classifies the LED's into 10 different types of
0 to 9. All the attributes are nominal types and all have 2 unique values 0 or 1. There are in total 25 attributes out of which
24 are the nominal 0 or 1 types and the last one is the class of the lED light.
For simplification, all the attributes have been stored in the CSV file which has
24 columns, the last column is the
class and the rest
23 contain the information about the LED.
Following files are available in the
7500samples) File that should be used for training. It contains the feature representation and the respective classes.
2500samples) File that will be used for testing. Unlike the training file it contains only the feature representation of hands and not the classses.
- Prepare a python file which should produce a csv file with name "submission.csv" containing header as "class" and predicted value as digit between [0…9] representing one of the 10 possible classes to which the LED belongs.
- Your submission should read the train and test data (available as environment variables) and should write 'submission.csv' containing the predictions for the test set.
- Sample submission format available in resources section. Make your first submission here 🚀 !!
🖊 Evaluation Criteria
During evaluation F1 score will be used to test the efficiency of the model where,
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