ml-finance-python

python scripts for finance machine learning

git clone https://9o.is/git/ml-finance-python.git

02_kmeans_implementation.ipynb

(229563B)


      1 {
      2  "cells": [
      3   {
      4    "cell_type": "markdown",
      5    "metadata": {},
      6    "source": [
      7     "# k-Means Clustering: Implementation"
      8    ]
      9   },
     10   {
     11    "cell_type": "markdown",
     12    "metadata": {},
     13    "source": [
     14     "k-Means is the most well-known clustering algorithm and was first proposed by Stuart Lloyd at Bell Labs in 1957. \n",
     15     "\n",
     16     "The algorithm finds K centroids and assigns each data point to exactly one cluster with the goal of minimizing the within-cluster variance (called inertia). It typically uses Euclidean distance but other metrics can also be used. k-Means assumes that clusters are spherical and of equal size and ignores the covariance among features.\n",
     17     "\n",
     18     "The problem is computationally difficult (np-hard) because there are š¾N ways to partition the N observations into K clusters. The standard iterative algorithm delivers a local optimum for a given K and proceeds as follows:\n",
     19     "1. Randomly define K cluster centers and assign points to nearest centroid\n",
     20     "2. Repeat: \n",
     21     "    1. For each cluster, compute the centroid as the average of the features\n",
     22     "    2. Assign each observation to the closest centroid\n",
     23     "3. Convergence: assignments (or within-cluster variation) don’t change"
     24    ]
     25   },
     26   {
     27    "cell_type": "markdown",
     28    "metadata": {},
     29    "source": [
     30     "This notebook demonstrates how to code the algorithm using python and visualizes the algorithm’s iterative optimization."
     31    ]
     32   },
     33   {
     34    "cell_type": "markdown",
     35    "metadata": {},
     36    "source": [
     37     "## Imports & Settings"
     38    ]
     39   },
     40   {
     41    "cell_type": "code",
     42    "execution_count": 11,
     43    "metadata": {
     44     "ExecuteTime": {
     45      "end_time": "2018-12-27T18:38:41.365367Z",
     46      "start_time": "2018-12-27T18:38:41.234632Z"
     47     },
     48     "slideshow": {
     49      "slide_type": "skip"
     50     }
     51    },
     52    "outputs": [],
     53    "source": [
     54     "%matplotlib inline\n",
     55     "import numpy as np\n",
     56     "from numpy.random import uniform, seed\n",
     57     "import pandas as pd\n",
     58     "import matplotlib.pyplot as plt\n",
     59     "from sklearn.datasets import make_blobs\n",
     60     "import warnings\n",
     61     "from time import sleep\n",
     62     "from scipy.spatial.distance import cdist"
     63    ]
     64   },
     65   {
     66    "cell_type": "code",
     67    "execution_count": 12,
     68    "metadata": {
     69     "ExecuteTime": {
     70      "end_time": "2018-12-27T18:38:41.368453Z",
     71      "start_time": "2018-12-27T18:38:41.366705Z"
     72     },
     73     "slideshow": {
     74      "slide_type": "skip"
     75     }
     76    },
     77    "outputs": [],
     78    "source": [
     79     "warnings.filterwarnings('ignore')\n",
     80     "seed(42)"
     81    ]
     82   },
     83   {
     84    "cell_type": "code",
     85    "execution_count": 13,
     86    "metadata": {
     87     "ExecuteTime": {
     88      "end_time": "2018-12-27T18:38:41.378085Z",
     89      "start_time": "2018-12-27T18:38:41.369600Z"
     90     },
     91     "slideshow": {
     92      "slide_type": "skip"
     93     }
     94    },
     95    "outputs": [],
     96    "source": [
     97     "SMALL_SIZE = 8\n",
     98     "MEDIUM_SIZE = 10\n",
     99     "BIGGER_SIZE = 12\n",
    100     "\n",
    101     "plt.rc('font', size=MEDIUM_SIZE)\n",
    102     "plt.rc('axes', titlesize=MEDIUM_SIZE)  \n",
    103     "plt.rc('axes', labelsize=SMALL_SIZE)\n",
    104     "plt.rc('xtick', labelsize=SMALL_SIZE)  \n",
    105     "plt.rc('ytick', labelsize=SMALL_SIZE)"
    106    ]
    107   },
    108   {
    109    "cell_type": "markdown",
    110    "metadata": {
    111     "slideshow": {
    112      "slide_type": "slide"
    113     }
    114    },
    115    "source": [
    116     "## 2D Cluster Demo"
    117    ]
    118   },
    119   {
    120    "cell_type": "code",
    121    "execution_count": 14,
    122    "metadata": {
    123     "ExecuteTime": {
    124      "end_time": "2018-12-27T18:38:41.389522Z",
    125      "start_time": "2018-12-27T18:38:41.379332Z"
    126     },
    127     "slideshow": {
    128      "slide_type": "fragment"
    129     }
    130    },
    131    "outputs": [],
    132    "source": [
    133     "def sample_clusters(n_points=500, n_dimensions=2, n_clusters=5, \n",
    134     "                    cluster_std=1):\n",
    135     "    data, labels = make_blobs(n_samples=n_points, \n",
    136     "                               n_features=n_dimensions, \n",
    137     "                               centers=n_clusters, \n",
    138     "                               cluster_std=cluster_std, \n",
    139     "                               random_state=42)\n",
    140     "    return data, labels"
    141    ]
    142   },
    143   {
    144    "cell_type": "code",
    145    "execution_count": 15,
    146    "metadata": {
    147     "ExecuteTime": {
    148      "end_time": "2018-12-27T18:38:41.550197Z",
    149      "start_time": "2018-12-27T18:38:41.390729Z"
    150     },
    151     "scrolled": false,
    152     "slideshow": {
    153      "slide_type": "skip"
    154     }
    155    },
    156    "outputs": [
    157     {
    158      "data": {
    159       "image/png": 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\n",
    160       "text/plain": [
    161        "<Figure size 432x288 with 1 Axes>"
    162       ]
    163      },
    164      "metadata": {
    165       "needs_background": "light"
    166      },
    167      "output_type": "display_data"
    168     }
    169    ],
    170    "source": [
    171     "data, labels = sample_clusters(n_points=250, n_dimensions=2, n_clusters=3, cluster_std=3)\n",
    172     "x, y = data.T\n",
    173     "\n",
    174     "plt.figure()\n",
    175     "plt.scatter(x, y, s=10)\n",
    176     "plt.title('Sample Data', fontsize=14);"
    177    ]
    178   },
    179   {
    180    "cell_type": "markdown",
    181    "metadata": {
    182     "slideshow": {
    183      "slide_type": "slide"
    184     }
    185    },
    186    "source": [
    187     "## K-Means Implementation"
    188    ]
    189   },
    190   {
    191    "cell_type": "markdown",
    192    "metadata": {
    193     "slideshow": {
    194      "slide_type": "fragment"
    195     }
    196    },
    197    "source": [
    198     "### Assign Points to closest Centroid"
    199    ]
    200   },
    201   {
    202    "cell_type": "code",
    203    "execution_count": 16,
    204    "metadata": {
    205     "ExecuteTime": {
    206      "end_time": "2018-12-27T18:38:41.553197Z",
    207      "start_time": "2018-12-27T18:38:41.551207Z"
    208     },
    209     "slideshow": {
    210      "slide_type": "fragment"
    211     }
    212    },
    213    "outputs": [],
    214    "source": [
    215     "def assign_points(centroids, data):\n",
    216     "    dist = cdist(data, centroids)        # all pairwise distances\n",
    217     "    assignments = np.argmin(dist, axis=1)   # centroid with min distance\n",
    218     "    return assignments"
    219    ]
    220   },
    221   {
    222    "cell_type": "markdown",
    223    "metadata": {
    224     "slideshow": {
    225      "slide_type": "slide"
    226     }
    227    },
    228    "source": [
    229     "### Move Centroids to best represent Clusters"
    230    ]
    231   },
    232   {
    233    "cell_type": "code",
    234    "execution_count": 17,
    235    "metadata": {
    236     "ExecuteTime": {
    237      "end_time": "2018-12-27T18:38:41.563528Z",
    238      "start_time": "2018-12-27T18:38:41.554131Z"
    239     },
    240     "slideshow": {
    241      "slide_type": "fragment"
    242     }
    243    },
    244    "outputs": [],
    245    "source": [
    246     "def optimize_centroids(data, assignments):\n",
    247     "    data_combined = np.column_stack((assignments.reshape(-1, 1), data))\n",
    248     "    centroids = pd.DataFrame(data=data_combined).groupby(0).mean()\n",
    249     "    return centroids.values"
    250    ]
    251   },
    252   {
    253    "cell_type": "markdown",
    254    "metadata": {
    255     "slideshow": {
    256      "slide_type": "slide"
    257     }
    258    },
    259    "source": [
    260     "### Measure Distance from Points to Centroids"
    261    ]
    262   },
    263   {
    264    "cell_type": "code",
    265    "execution_count": 18,
    266    "metadata": {
    267     "ExecuteTime": {
    268      "end_time": "2018-12-27T18:38:41.576066Z",
    269      "start_time": "2018-12-27T18:38:41.564850Z"
    270     },
    271     "slideshow": {
    272      "slide_type": "fragment"
    273     }
    274    },
    275    "outputs": [],
    276    "source": [
    277     "def distance_to_center(centroids, data, assignments):\n",
    278     "    distance = 0\n",
    279     "    for c, centroid in enumerate(centroids):\n",
    280     "        assigned_points = data[assignments == c, :]\n",
    281     "        distance += np.sum(cdist(assigned_points, centroid.reshape(-1, 2)))\n",
    282     "    return distance"
    283    ]
    284   },
    285   {
    286    "cell_type": "markdown",
    287    "metadata": {
    288     "slideshow": {
    289      "slide_type": "slide"
    290     }
    291    },
    292    "source": [
    293     "### Plot Clusters Dynamically"
    294    ]
    295   },
    296   {
    297    "cell_type": "code",
    298    "execution_count": 19,
    299    "metadata": {
    300     "ExecuteTime": {
    301      "end_time": "2018-12-27T18:38:41.591748Z",
    302      "start_time": "2018-12-27T18:38:41.578275Z"
    303     },
    304     "slideshow": {
    305      "slide_type": "fragment"
    306     }
    307    },
    308    "outputs": [],
    309    "source": [
    310     "def plot_clusters(x, y, labels, centroids, assignments, distance, \n",
    311     "                  iteration, step, ax, delay=2):\n",
    312     "    ax.clear()\n",
    313     "    ax.scatter(x, y, c=labels, s=15)\n",
    314     "    # plot cluster centers\n",
    315     "    centroid_x, centroid_y = centroids.T\n",
    316     "    ax.scatter(*centroids.T, marker='o',  c='w', s=200, \n",
    317     "               edgecolor='k', zorder=9)\n",
    318     "    for label, c in enumerate(centroids):\n",
    319     "        ax.scatter(c[0], c[1], marker='${}$'.format(label), s=50, \n",
    320     "                   edgecolor='k', zorder=10)\n",
    321     "    # plot links to cluster centers\n",
    322     "    for i, label in enumerate(assignments):\n",
    323     "        ax.plot([x[i], centroid_x[label]], [y[i], centroid_y[label]], \n",
    324     "                ls='--', color='white', lw=0.5)\n",
    325     "    \n",
    326     "    ax.set_title('Iteration: {} | {} | Inertia: {:,.2f}'.format(iteration, \n",
    327     "                                        step,  distance), fontsize=14)\n",
    328     "    fig.canvas.draw()\n",
    329     "    sleep(delay)"
    330    ]
    331   },
    332   {
    333    "cell_type": "markdown",
    334    "metadata": {
    335     "slideshow": {
    336      "slide_type": "slide"
    337     }
    338    },
    339    "source": [
    340     "### Run K-Means Experiment"
    341    ]
    342   },
    343   {
    344    "cell_type": "markdown",
    345    "metadata": {},
    346    "source": [
    347     "The following figures highlights how the resulting centroids partition the feature space into areas called Voronoi that delineate the clusters."
    348    ]
    349   },
    350   {
    351    "cell_type": "markdown",
    352    "metadata": {},
    353    "source": [
    354     "k-Means requires continuous or one-hot encoded categorical variables. Distance metrics are typically sensitive to scale so that standardizing features is necessary to make sure they have equal weight."
    355    ]
    356   },
    357   {
    358    "cell_type": "markdown",
    359    "metadata": {},
    360    "source": [
    361     "The result is optimal for the given initialization but alternative starting positions will produce different results. Hence, we compute multiple clusterings from different initial values and select the solution that minimizes within-cluster variance."
    362    ]
    363   },
    364   {
    365    "cell_type": "code",
    366    "execution_count": 20,
    367    "metadata": {
    368     "ExecuteTime": {
    369      "end_time": "2018-12-27T18:59:31.641007Z",
    370      "start_time": "2018-12-27T18:59:08.409483Z"
    371     },
    372     "slideshow": {
    373      "slide_type": "fragment"
    374     }
    375    },
    376    "outputs": [
    377     {
    378      "data": {
    379       "image/png": 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\n",
    380       "text/plain": [
    381        "<Figure size 720x720 with 1 Axes>"
    382       ]
    383      },
    384      "metadata": {
    385       "needs_background": "light"
    386      },
    387      "output_type": "display_data"
    388     }
    389    ],
    390    "source": [
    391     "n_clusters = 3\n",
    392     "data, labels = sample_clusters(n_points=250, n_dimensions=2, n_clusters=n_clusters, cluster_std=3)\n",
    393     "x, y = data.T\n",
    394     "\n",
    395     "x_init = uniform(x.min(), x.max(), size=n_clusters)\n",
    396     "y_init = uniform(y.min(), y.max(), size=n_clusters)\n",
    397     "centroids = np.column_stack((x_init, y_init))\n",
    398     "distance = np.sum(np.min(cdist(data, centroids), axis=1))\n",
    399     "\n",
    400     "fig, ax = plt.subplots(figsize=(10,10))\n",
    401     "iteration, tolerance, delta = 0, 1e-4, np.inf\n",
    402     "while delta > tolerance:\n",
    403     "    assignments = assign_points(centroids, data)\n",
    404     "    plot_clusters(x, y, labels, centroids, assignments, distance, \n",
    405     "                  iteration, step='Assign Points', ax=ax)\n",
    406     "    centroids = optimize_centroids(data, assignments)\n",
    407     "    delta = distance - distance_to_center(centroids, data, assignments)\n",
    408     "    distance -= delta\n",
    409     "    plot_clusters(x, y, labels, centroids, assignments, distance, \n",
    410     "                  iteration, step='Optimize Centers', ax=ax)\n",
    411     "    iteration += 1\n",
    412     "plt.savefig('kmeans_before', dpi=300)    "
    413    ]
    414   },
    415   {
    416    "cell_type": "markdown",
    417    "metadata": {
    418     "slideshow": {
    419      "slide_type": "slide"
    420     }
    421    },
    422    "source": [
    423     "### Plot Voronoi Tesselation"
    424    ]
    425   },
    426   {
    427    "cell_type": "code",
    428    "execution_count": 21,
    429    "metadata": {
    430     "ExecuteTime": {
    431      "end_time": "2018-12-27T18:39:14.265425Z",
    432      "start_time": "2018-12-27T18:39:14.259673Z"
    433     },
    434     "slideshow": {
    435      "slide_type": "fragment"
    436     }
    437    },
    438    "outputs": [],
    439    "source": [
    440     "def plot_voronoi(x, y, labels, centroids, assignments, distance, iteration, step, ax, delay=1):\n",
    441     "    ax.clear()\n",
    442     "    ax.scatter(x, y, c=labels, s=15)\n",
    443     "    # plot cluster centers\n",
    444     "    ax.scatter(*centroids.T, marker='o',  c='w', s=200, edgecolor='k', zorder=9)\n",
    445     "    for i, c in enumerate(centroids):\n",
    446     "        ax.scatter(c[0], c[1], marker='${}$'.format(i), s=50, \n",
    447     "                   edgecolor='k', zorder=10)   \n",
    448     "\n",
    449     "    # plot links to centroid\n",
    450     "    cx, cy = centroids.T\n",
    451     "    for i, label in enumerate(assignments):\n",
    452     "        ax.plot([x[i], cx[label]], [y[i], cy[label]], ls='--', \n",
    453     "                color='white', lw=0.5)\n",
    454     "    \n",
    455     "    # plot voronoi\n",
    456     "    xx, yy = np.meshgrid(np.arange(x.min() - 1, x.max() + 1, .01), \n",
    457     "                         np.arange(y.min() - 1, y.max() + 1, .01))\n",
    458     "    Z = assign_points(centroids, np.c_[xx.ravel(),  yy.ravel()]).reshape(xx.shape)\n",
    459     "    plt.imshow(Z, interpolation='nearest', extent=(xx.min(), xx.max(), yy.min(), yy.max()),\n",
    460     "       cmap=plt.cm.viridis, aspect='auto', origin='lower', alpha=.2)\n",
    461     "    \n",
    462     "    ax.set_title('Iteration: {} | {} | Distance: {:,.1f}'.format(iteration, step, distance))\n",
    463     "    fig.canvas.draw()\n",
    464     "    sleep(delay)"
    465    ]
    466   },
    467   {
    468    "cell_type": "markdown",
    469    "metadata": {
    470     "slideshow": {
    471      "slide_type": "slide"
    472     }
    473    },
    474    "source": [
    475     "### Run Voronoi Experiment"
    476    ]
    477   },
    478   {
    479    "cell_type": "code",
    480    "execution_count": 22,
    481    "metadata": {
    482     "ExecuteTime": {
    483      "end_time": "2018-12-27T18:59:46.085598Z",
    484      "start_time": "2018-12-27T18:59:31.642375Z"
    485     },
    486     "slideshow": {
    487      "slide_type": "fragment"
    488     }
    489    },
    490    "outputs": [
    491     {
    492      "data": {
    493       "image/png": 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\n",
    494       "text/plain": [
    495        "<Figure size 864x864 with 1 Axes>"
    496       ]
    497      },
    498      "metadata": {
    499       "needs_background": "light"
    500      },
    501      "output_type": "display_data"
    502     }
    503    ],
    504    "source": [
    505     "n_clusters = 3\n",
    506     "data, labels = sample_clusters(n_points=250, n_dimensions=2, \n",
    507     "                               n_clusters=n_clusters, cluster_std=3)\n",
    508     "x, y = data.T\n",
    509     "\n",
    510     "x_init = uniform(x.min(), x.max(), size=n_clusters)\n",
    511     "y_init = uniform(y.min(), y.max(), size=n_clusters)\n",
    512     "centroids = np.column_stack((x_init, y_init))\n",
    513     "distance = np.sum(np.min(cdist(data, centroids), axis=1))\n",
    514     "\n",
    515     "fig, ax = plt.subplots(figsize=(12,12))\n",
    516     "iteration, tolerance, delta = 0, 1e-4, np.inf\n",
    517     "while delta > tolerance:\n",
    518     "    assignments = assign_points(centroids, data)\n",
    519     "    plot_voronoi(x, y, labels, centroids, assignments, distance, \n",
    520     "                 iteration, step='Assign Data', ax=ax)\n",
    521     "    centroids = optimize_centroids(data, assignments)\n",
    522     "    delta = distance - distance_to_center(centroids, data, assignments)\n",
    523     "    distance -= delta\n",
    524     "    plot_voronoi(x, y, labels, centroids, assignments, distance, \n",
    525     "                 iteration, step='Optimize Centroids', ax=ax)\n",
    526     "    iteration += 1\n",
    527     "plt.savefig('kmeans', dpi=300)    "
    528    ]
    529   },
    530   {
    531    "cell_type": "markdown",
    532    "metadata": {},
    533    "source": [
    534     "## Strengths & Weaknesses"
    535    ]
    536   },
    537   {
    538    "cell_type": "markdown",
    539    "metadata": {},
    540    "source": [
    541     "The strengths of k-Means include \n",
    542     "- its wide range of applicability, \n",
    543     "- fast convergence and \n",
    544     "- linear scalability to large data while producing clusters of even size. \n",
    545     "\n",
    546     "The weaknesses include \n",
    547     "- the need to tune the hyperparameter k, \n",
    548     "- it is not guaranteed to find a global optimum, \n",
    549     "- makes the restrictive assumption that clusters are spheres and features are not correlated. \n",
    550     "- It is also sensitive to outliers."
    551    ]
    552   },
    553   {
    554    "cell_type": "code",
    555    "execution_count": null,
    556    "metadata": {},
    557    "outputs": [],
    558    "source": []
    559   }
    560  ],
    561  "metadata": {
    562   "celltoolbar": "Slideshow",
    563   "hide_input": false,
    564   "kernelspec": {
    565    "display_name": "Python 3",
    566    "language": "python",
    567    "name": "python3"
    568   },
    569   "language_info": {
    570    "codemirror_mode": {
    571     "name": "ipython",
    572     "version": 3
    573    },
    574    "file_extension": ".py",
    575    "mimetype": "text/x-python",
    576    "name": "python",
    577    "nbconvert_exporter": "python",
    578    "pygments_lexer": "ipython3",
    579    "version": "3.7.0"
    580   },
    581   "toc": {
    582    "base_numbering": 1,
    583    "nav_menu": {},
    584    "number_sections": true,
    585    "sideBar": true,
    586    "skip_h1_title": true,
    587    "title_cell": "Table of Contents",
    588    "title_sidebar": "Contents",
    589    "toc_cell": false,
    590    "toc_position": {},
    591    "toc_section_display": true,
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