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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"<h1 id=\"Data-distributions-where-Kmeans-clustering-fails\">Data distributions where <a href=\"https://en.wikipedia.org/wiki/K-means_clustering\" style=\"text-decoration:none;\" target=\"_blank\">Kmeans clustering</a> fails<a class=\"anchor-link\" href=\"#Data-distributions-where-Kmeans-clustering-fails\">&#182;</a></h1><h1 id=\"Can-DBSCAN-be-a-solution\">Can <a href=\"https://en.wikipedia.org/wiki/DBSCAN\" style=\"text-decoration:none;\" target=\"_blank\">DBSCAN</a> be a solution?<a class=\"anchor-link\" href=\"#Can-DBSCAN-be-a-solution\">&#182;</a></h1>"
]
},
{
##############################################################################
# title : Download and create raster stack CRU CL2.0 Data.R;
# purpose : create R raster stack of CRU CL 2.0 data;
# producer : prepared by A. Sparks;
# last update : in Los Baños, Laguna, PI May 2014;
# inputs : CRU CL2.0 Climate data;
# outputs : ;
# remarks 1 : Downloads and calculates min/max T and generates raster stacks of precip, min/max/mean T;
##############################################################################