{
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   "source": [
    "Train Models on Large Datasets\n",
    "==============================\n",
    "\n",
    "Most estimators in scikit-learn are designed to work with NumPy arrays or scipy sparse matricies.\n",
    "These data structures must fit in the RAM on a single machine.\n",
    "\n",
    "Estimators implemented in Dask-ML work well with Dask Arrays and DataFrames. This can be much larger than a single machine's RAM. They can be distributed in memory on a cluster of machines."
   ]
  },
  {
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   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
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       "                            <strong>Local directory: </strong> /home/runner/work/dask-examples/dask-examples/machine-learning/dask-worker-space/worker-by3a7q7t\n",
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       "<Client: 'inproc://10.1.1.64/9835/1' processes=1 threads=4, memory=1.86 GiB>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from dask.distributed import Client\n",
    "\n",
    "# Scale up: connect to your own cluster with more resources\n",
    "# see http://dask.pydata.org/en/latest/setup.html\n",
    "client = Client(processes=False, threads_per_worker=4,\n",
    "                n_workers=1, memory_limit='2GB')\n",
    "client"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-27T19:23:49.907964Z",
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     "shell.execute_reply": "2022-07-27T19:23:51.306648Z"
    }
   },
   "outputs": [],
   "source": [
    "import dask_ml.datasets\n",
    "import dask_ml.cluster\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this example, we'll use `dask_ml.datasets.make_blobs` to generate some random *dask* arrays."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
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     "shell.execute_reply": "2022-07-27T19:23:51.604752Z"
    }
   },
   "outputs": [
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       "dask.array<concatenate, shape=(1000000, 2), dtype=float64, chunksize=(100000, 2), chunktype=numpy.ndarray>"
      ]
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     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Scale up: increase n_samples or n_features\n",
    "X, y = dask_ml.datasets.make_blobs(n_samples=1000000,\n",
    "                                   chunks=100000,\n",
    "                                   random_state=0,\n",
    "                                   centers=3)\n",
    "X = X.persist()\n",
    "X"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We'll use the k-means implemented in Dask-ML to cluster the points. It uses the `k-means||` (read: \"k-means parallel\") initialization algorithm, which scales better than `k-means++`. All of the computation, both during and after initialization, can be done in parallel."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-27T19:23:51.610439Z",
     "iopub.status.busy": "2022-07-27T19:23:51.610233Z",
     "iopub.status.idle": "2022-07-27T19:23:54.806083Z",
     "shell.execute_reply": "2022-07-27T19:23:54.805510Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/share/miniconda3/envs/dask-examples/lib/python3.9/site-packages/dask/base.py:1283: UserWarning: Running on a single-machine scheduler when a distributed client is active might lead to unexpected results.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "KMeans(init_max_iter=2, n_clusters=3, oversampling_factor=10)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "km = dask_ml.cluster.KMeans(n_clusters=3, init_max_iter=2, oversampling_factor=10)\n",
    "km.fit(X)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We'll plot a sample of points, colored by the cluster each falls into."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-27T19:23:54.809911Z",
     "iopub.status.busy": "2022-07-27T19:23:54.809095Z",
     "iopub.status.idle": "2022-07-27T19:23:55.095558Z",
     "shell.execute_reply": "2022-07-27T19:23:55.094943Z"
    }
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "ax.scatter(X[::1000, 0], X[::1000, 1], marker='.', c=km.labels_[::1000],\n",
    "           cmap='viridis', alpha=0.25);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For all the estimators implemented in Dask-ML, see the [API documentation](https://ml.dask.org/modules/api.html#)."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}