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python Programming Glossary: distancesPython: tf-idf-cosine: to find document similarity http://stackoverflow.com/questions/12118720/python-tf-idf-cosine-to-find-document-similarity in Compressed Sparse Row format Now to find the cosine distances of one document e.g. the first in the dataset and all of the..
Working with big data in python and numpy, not enough ram, how to save partial results on disc? http://stackoverflow.com/questions/16149803/working-with-big-data-in-python-and-numpy-not-enough-ram-how-to-save-partial-r of ram. Of course I do creating the matrix for pairwise distances on 200k data takes alot of memory. Here comes the catch I would..
more efficient way to calculate distance in numpy? http://stackoverflow.com/questions/17527340/more-efficient-way-to-calculate-distance-in-numpy distance in numpy i have a question on how to calculate distances in numpy as fast as it can def getR1 VVm VVs HHm HHs t0 time.time..
Euclidean distance between points in two different Numpy arrays, not within http://stackoverflow.com/questions/1871536/euclidean-distance-between-points-in-two-different-numpy-arrays-not-within loops through each coordinate xy in xy1 and calculates the distances between that coordinate and the other coordinates. mindist numpy.zeros.. later scipy.spatial.distance.cdist X Y gives all pairs of distances for X and Y 2 dim 3 dim ... It also does 22 different norms..
Inverse Distance Weighted (IDW) Interpolation with Python http://stackoverflow.com/questions/3104781/inverse-distance-weighted-idw-interpolation-with-python functionality to locate the closest points and calculate distances. Am I missing something obvious Is there a python module I haven't.. a query point q finds the 3 data points nearest q at distances d1 d2 d3 and returns the IDW average of the values z1 z2 z3.. z1 d1 z2 d2 z3 d3 1 d1 1 d2 1 d3 .55 z1 .27 z2 .18 z3 for distances 1 2 3 q may be one point or a batch of points. eps approximate..
String concatenation vs. string substitution in Python http://stackoverflow.com/questions/376461/string-concatenation-vs-string-substitution-in-python
Is it possible to specify your own distance function using Scikits.Learn K-Means Clustering? http://stackoverflow.com/questions/5529625/is-it-possible-to-specify-your-own-distance-function-using-scikits-learn-k-means Here's a small kmeans that uses any of the 20 odd distances in scipy.spatial.distance or a user function. Comments would.. 10 metric euclidean p 2 verbose 1 centres Xtocentre distances kmeans X initial centres ... in X N x dim may be sparse centres.. mod cdist for 0 p 1 too verbose 0 silent 2 prints running distances out centres k x dim Xtocentre each X its nearest centre ints..
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