view code/Hierarchical Clustering.ipynb @ 0:7d69c0d6f4c9

Initial

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   "source": [
    "from matplotlib import pyplot as plt\n",
    "from scipy.cluster.hierarchy import dendrogram, linkage, cophenet\n",
    "from scipy.spatial.distance import pdist\n",
    "import numpy as np\n",
    "import csv\n",
    "\n",
    "dataFolder = '../data/'\n",
    "keyFile = 'AdobeNormalised'\n",
    "datapath = dataFolder + keyFile"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
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   "source": [
    "X = np.genfromtxt(datapath+'.csv', delimiter = ',', skip_header = 1)\n",
    "filenames = np.loadtxt(datapath+'_filenames.csv', dtype = str)\n",
    "labels = np.loadtxt(datapath+'_labels.csv', dtype = str)\n",
    "features = np.loadtxt(datapath+'_features.csv', dtype = str)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
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   "outputs": [],
   "source": [
    "print X.shape\n",
    "print filenames.shape\n",
    "print features.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "Z = linkage(X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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