abhishek-ghose abhishek-ghose

	import numpy as np


	def kendall_w(scores):
	"""
	:param scores: rows correspond to category levels, e.g., for QS this would be unc. sampling, CAL etc, and the
	columns correspond to the scores.
	:return:
	"""
	if scores.ndim!=2:

	import numpy as np, itertools
	import pandas as pd
	import ot
	from matplotlib import pyplot as plt
	from matplotlib.collections import LineCollection
	import seaborn as sns; sns.set()
	from scipy.stats import multivariate_normal as mvn, norm
	from sklearn.cluster import KMeans
	import os
	from datetime import datetime