{
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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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   "source": [
    "%matplotlib inline"
   ]
  },
  {
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       "                            <strong>Local directory: </strong> /home/runner/work/dask-examples/dask-examples/machine-learning/dask-worker-space/worker-wgy1fljq\n",
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       "<Client: 'inproc://10.1.0.7/9947/1' 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": {
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     "shell.execute_reply": "2022-06-17T02:50:46.341685Z"
    }
   },
   "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": "2022-06-17T02:50:46.645426Z"
    }
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   "outputs": [
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       "dask.array<concatenate, shape=(1000000, 2), dtype=float64, chunksize=(100000, 2), chunktype=numpy.ndarray>"
      ]
     },
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     "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": "2022-06-17T02:50:46.651130Z",
     "iopub.status.busy": "2022-06-17T02:50:46.650928Z",
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     "shell.execute_reply": "2022-06-17T02:50:49.529065Z"
    }
   },
   "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": {
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     "shell.execute_reply": "2022-06-17T02:50:49.827943Z"
    }
   },
   "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
}