minor adjustments
This commit is contained in:
		| @ -22,7 +22,7 @@ | ||||
|   }, | ||||
|   { | ||||
|    "cell_type": "code", | ||||
|    "execution_count": 15, | ||||
|    "execution_count": 2, | ||||
|    "metadata": {}, | ||||
|    "outputs": [], | ||||
|    "source": [ | ||||
| @ -36,7 +36,7 @@ | ||||
|   }, | ||||
|   { | ||||
|    "cell_type": "code", | ||||
|    "execution_count": 2, | ||||
|    "execution_count": 3, | ||||
|    "metadata": {}, | ||||
|    "outputs": [], | ||||
|    "source": [ | ||||
| @ -60,7 +60,7 @@ | ||||
|   }, | ||||
|   { | ||||
|    "cell_type": "code", | ||||
|    "execution_count": 3, | ||||
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|    "source": [ | ||||
| @ -76,7 +76,7 @@ | ||||
|   }, | ||||
|   { | ||||
|    "cell_type": "code", | ||||
|    "execution_count": 4, | ||||
|    "execution_count": 5, | ||||
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| @ -99,7 +99,7 @@ | ||||
|   }, | ||||
|   { | ||||
|    "cell_type": "code", | ||||
|    "execution_count": 5, | ||||
|    "execution_count": 6, | ||||
|    "metadata": {}, | ||||
|    "outputs": [ | ||||
|     { | ||||
| @ -1191,7 +1191,7 @@ | ||||
|        "[68733 rows x 9 columns]" | ||||
|       ] | ||||
|      }, | ||||
|      "execution_count": 5, | ||||
|      "execution_count": 6, | ||||
|      "metadata": {}, | ||||
|      "output_type": "execute_result" | ||||
|     } | ||||
| @ -1210,7 +1210,7 @@ | ||||
|   }, | ||||
|   { | ||||
|    "cell_type": "code", | ||||
|    "execution_count": 6, | ||||
|    "execution_count": 7, | ||||
|    "metadata": {}, | ||||
|    "outputs": [], | ||||
|    "source": [ | ||||
| @ -1229,7 +1229,7 @@ | ||||
|   }, | ||||
|   { | ||||
|    "cell_type": "code", | ||||
|    "execution_count": 7, | ||||
|    "execution_count": 8, | ||||
|    "metadata": {}, | ||||
|    "outputs": [], | ||||
|    "source": [ | ||||
| @ -1247,7 +1247,7 @@ | ||||
|   }, | ||||
|   { | ||||
|    "cell_type": "code", | ||||
|    "execution_count": 8, | ||||
|    "execution_count": 9, | ||||
|    "metadata": {}, | ||||
|    "outputs": [], | ||||
|    "source": [ | ||||
| @ -1264,7 +1264,7 @@ | ||||
|   }, | ||||
|   { | ||||
|    "cell_type": "code", | ||||
|    "execution_count": 9, | ||||
|    "execution_count": 10, | ||||
|    "metadata": {}, | ||||
|    "outputs": [], | ||||
|    "source": [ | ||||
| @ -1277,18 +1277,11 @@ | ||||
|   }, | ||||
|   { | ||||
|    "cell_type": "code", | ||||
|    "execution_count": 10, | ||||
|    "execution_count": 12, | ||||
|    "metadata": {}, | ||||
|    "outputs": [], | ||||
|    "source": [ | ||||
|     "mlb_multi = MultiLabelBinarizer()\n", | ||||
|     "mlb_single = MultiLabelBinarizer()\n", | ||||
|     "\n", | ||||
|     "multi_labels = mlb_multi.fit_transform(emojis)\n", | ||||
|     "single_labels = mlb_single.fit_transform(np.array([latest(x) for x in emojis]))\n", | ||||
|     "\n", | ||||
|     "mlb = mlb_single if SINGLE_LABEL else mlb_multi\n", | ||||
|     "labels = single_labels if SINGLE_LABEL else multi_labels" | ||||
|     "labels = [emoji2sent(latest(x)) for x in emojis]" | ||||
|    ] | ||||
|   }, | ||||
|   { | ||||
| @ -1300,7 +1293,7 @@ | ||||
|   }, | ||||
|   { | ||||
|    "cell_type": "code", | ||||
|    "execution_count": 11, | ||||
|    "execution_count": 13, | ||||
|    "metadata": {}, | ||||
|    "outputs": [], | ||||
|    "source": [ | ||||
| @ -1341,7 +1334,7 @@ | ||||
|   }, | ||||
|   { | ||||
|    "cell_type": "code", | ||||
|    "execution_count": 12, | ||||
|    "execution_count": 14, | ||||
|    "metadata": {}, | ||||
|    "outputs": [], | ||||
|    "source": [ | ||||
| @ -1350,16 +1343,16 @@ | ||||
|   }, | ||||
|   { | ||||
|    "cell_type": "code", | ||||
|    "execution_count": 13, | ||||
|    "execution_count": 15, | ||||
|    "metadata": {}, | ||||
|    "outputs": [], | ||||
|    "source": [ | ||||
|     "y1_weights = np.array([(sum([emoji_weights[e] for e in e_list]) / len(e_list)) if len(e_list) > 0 else 0 for e_list in mlb.inverse_transform(y1)])" | ||||
|     "y1_weights = np.array([(sum([emoji_weights[e] for e in e_list]) / len(e_list)) if len(e_list) > 0 else 0 for e_list in sent2emoji(y1)])" | ||||
|    ] | ||||
|   }, | ||||
|   { | ||||
|    "cell_type": "code", | ||||
|    "execution_count": 14, | ||||
|    "execution_count": 16, | ||||
|    "metadata": {}, | ||||
|    "outputs": [], | ||||
|    "source": [ | ||||
| @ -1619,7 +1612,9 @@ | ||||
|    "outputs": [], | ||||
|    "source": [ | ||||
|     "# build a dataframe to visualize test results:\n", | ||||
|     "testlist = pd.DataFrame({'text': Xt1, 'teacher': (mlb_single if SINGLE_LABEL else mlb).inverse_transform(yt1), 'predict': (mlb_single if SINGLE_LABEL else mlb).inverse_transform(binary_pred)})" | ||||
|     "testlist = pd.DataFrame({'text': Xt1, \n", | ||||
|     "                         'teacher': mlb_single.inverse_transform(yt1) if SINGLE_LABEL else sent2emoji(yt1), \n", | ||||
|     "                         'predict': mlb_single.inverse_transform(binary_pred) if SINGLE_LABEL else sent2emoji(binary_pred)})" | ||||
|    ] | ||||
|   }, | ||||
|   { | ||||
| @ -2214,7 +2209,7 @@ | ||||
|     "        \n", | ||||
|     "        binary_pred = np.array(binary_pred)\n", | ||||
|     "        \n", | ||||
|     "        display(Markdown(\"# \" + str((mlb_single if SINGLE_LABEL else mlb).inverse_transform(binary_pred))))\n", | ||||
|     "        display(Markdown(\"# \" + str(mlb_single.inverse_transform(binary_pred) if SINGLE_LABEL else sent2emoji(binary_pred))))\n", | ||||
|     "\n", | ||||
|     "b.on_click(handle_submit)\n", | ||||
|     "    \n", | ||||
|  | ||||
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