Keerthi Vasan GC kvgc

Regressor comparison

I wrote a blog post about this here.

I tweeted about it here and again

Inspired, of course, by the various wonderful comparisons in the sklearn docs, like this one for classifiers.

	import numpy as np

	from numpy.linalg import norm
	from sentence_transformers import SentenceTransformer

	# Define the model we want to use (it'll download itself)
	model = SentenceTransformer('sentence-transformers/all-MiniLM-L6-v2')

	sentences = [
	"That is a very happy person",

	from PyPDF2.generic import (
	DictionaryObject,
	NumberObject,
	FloatObject,
	NameObject,
	TextStringObject,
	ArrayObject
	)

	# x1, y1 starts in bottom left corner

	'''
	Most heatmap tutorials I found online use pyplot.pcolormesh with random sets of
	data from Numpy; I just needed to plot x, y, z values stored in lists--without
	all the Numpy mumbo jumbo. Here I have code to plot intensity on a 2D array, and
	I only use Numpy where I need to (pcolormesh expects Numpy arrays as inputs).
	'''
	import matplotlib.pyplot as plt
	import numpy as np

	#here's our data to plot, all normal Python lists

	# taken from http://www.piware.de/2011/01/creating-an-https-server-in-python/
	# generate server.xml with the following command:
	# openssl req -new -x509 -keyout server.pem -out server.pem -days 365 -nodes
	# run as follows:
	# python simple-https-server.py
	# then in your browser, visit:
	# https://localhost:4443

	import BaseHTTPServer, SimpleHTTPServer
	import ssl