vanamalivanam

vanamalivanam / forecasting_metrics.py

Created November 18, 2024 01:27 — forked from bshishov/forecasting_metrics.py

Python Numpy functions for most common forecasting metrics

	import numpy as np

	EPSILON = 1e-10


	def _error(actual: np.ndarray, predicted: np.ndarray):
	""" Simple error """
	return actual - predicted

vanamalivanam / minmaxabssign.txt

Created December 23, 2021 00:57 — forked from paniq/minmaxabssign.txt

useful min/max/abs/sign identities

	max(-x,-y) = -min(x,y)
	min(-x,-y) = -max(x,y)

	abs(x) = abs(-x)
	abs(x) = max(x,-x) = -min(x,-x)
	abs(xa) = if (a >= 0) abs(x)a
	(a < 0) -abs(x)*a

	// basically any commutative operation
	min(x,y) + max(x,y) = x + y

vanamalivanam / multiclass_svm.py

Created December 23, 2021 00:55 — forked from mblondel/multiclass_svm.py

Multiclass SVMs

	"""
	Multiclass SVMs (Crammer-Singer formulation).

	A pure Python re-implementation of:

	Large-scale Multiclass Support Vector Machine Training via Euclidean Projection onto the Simplex.
	Mathieu Blondel, Akinori Fujino, and Naonori Ueda.
	ICPR 2014.
	http://www.mblondel.org/publications/mblondel-icpr2014.pdf
	"""

vanamalivanam / check_convex.py

Created December 23, 2021 00:51 — forked from mblondel/check_convex.py

A small script to get numerical evidence that a function is convex

	# Authors: Mathieu Blondel, Vlad Niculae
	# License: BSD 3 clause

	import numpy as np


	def _gen_pairs(gen, max_iter, max_inner, random_state, verbose):
	rng = np.random.RandomState(random_state)

	# if tuple, interpret as randn

vanamalivanam / svm.py

Created December 23, 2021 00:50 — forked from mblondel/svm.py

Support Vector Machines

vanamalivanam / knn_impute.py

Created January 11, 2018 16:35 — forked from YohanObadia/knn_impute.py

Imputation of missing values with knn.

	import numpy as np
	import pandas as pd
	from collections import defaultdict
	from scipy.stats import hmean
	from scipy.spatial.distance import cdist
	from scipy import stats
	import numbers


	def weighted_hamming(data):