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CaptainAshis/dt_feature92.py

Last active September 27, 2018 10:44
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dt_feature92 ros fastai
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dt_feature92.py
# Approach 1
# One approach is to take the last 25% of rows (sorted by date) as our validation set.
train_ratio = 0.75
# train_ratio = 0.9
train_size = int(samp_size * train_ratio); train_size
val_idx = list(range(train_size, len(df)))
# Approach 2:- Just the last 2 weeks of data
val_idx = np.flatnonzero(
(df.index<=datetime.datetime(2014,9,17)) & (df.index>=datetime.datetime(2014,8,1)))
val_idx=[0]
# We will go with Approach 2
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