Make error message on invalid training column values more clear

[fedarko]

@vjcantu and I ran into this today -- if values in this column are labelled e.g. train and test, then 0 Train samples are identified (see line 189 below) and then later on Tensorflow fails with an obscure error that num_classes should be positive, got 0.

songbird/songbird/util.py

Lines 178 to 197 in 22ec2b5

	def split_training(dense_table, metadata, design, training_column=None,
	num_random_test_examples=10, seed=None):
	if training_column is None:
	np.random.seed(seed)
	idx = np.random.random(design.shape[0])
	i = np.argsort(idx)[num_random_test_examples]
	threshold = idx[i]
	train_idx = ~(idx < threshold)
	else:
	train_idx = metadata.loc[design.index, training_column] == "Train"
	trainX = design.loc[train_idx].values
	testX = design.loc[~train_idx].values
	trainY = dense_table.loc[train_idx].values
	testY = dense_table.loc[~train_idx].values
	return trainX, testX, trainY, testY

Even if we'd prefer to leave this as case sensitive, it might be good to add a note to the README/FAQs explaining where this error comes from and/or that the training column stuff is case sensitive.

[mortonjt]

👍 on the README update.

Note that we already have this explicit in the README and the CLI documentation (see this line). So maybe screenshots or notes on the exact casing is necessary.