do not use cache for knn model

Author: jreiberkyle

jupyter-notebooks/crop-classification/segment-knn.ipynb

@@ -690,7 +690,7 @@
    "source": [
     "Finally, we fit the classifier.\n",
     "\n",
-    "By default, the classifier is loaded from cache to save processing time. "
+    "We do not use cache for this model because the saved model is so bit (350M) and it does not take long to fit the model."
    ]
   },
   {
@@ -713,33 +713,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "clf_cache_file = os.path.join('pre-data', 'segment-knn-clf.sav')\n",
-    "\n",
-    "load_clf = True\n",
-    "if load_clf:\n",
-    "    assert os.path.isfile(clf_cache_file)\n",
-    "    clf = pickle.load(open(clf_cache_file, 'rb'))\n",
-    "else:\n",
-    "    clf = fit_classifier(train_scene_filename,\n",
-    "                         train_ground_truth_filename,\n",
-    "                         train_metadata_filename,\n",
-    "                         n_neighbors)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 25,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# optionally save ps clf model\n",
-    "save_clf = False\n",
-    "if save_clf:\n",
-    "    pickle.dump(clf, open(clf_cache_file, 'wb'))"
+    "clf = fit_classifier(train_scene_filename,\n",
+    "                     train_ground_truth_filename,\n",
+    "                     train_metadata_filename,\n",
+    "                     n_neighbors)"
    ]
   },
   {