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from models import Model
import utils
import pandas as pd
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# Paste your model here:
class CustomModel(Model):
def __init__(self):
super()
# Use self.state to store results of your learning
# It will be saved in filesystem and loaded after server restart
self.state = {}
def fit(self, dataframe: pd.DataFrame, segments: list, cache: dict) -> dict:
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pass
def predict(self, dataframe, cache: dict):
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return []