improved output and threshold
This commit is contained in:
		| @ -2,7 +2,7 @@ | ||||
|  "cells": [ | ||||
|   { | ||||
|    "cell_type": "code", | ||||
|    "execution_count": 42, | ||||
|    "execution_count": 149, | ||||
|    "metadata": {}, | ||||
|    "outputs": [], | ||||
|    "source": [ | ||||
| @ -15,7 +15,10 @@ | ||||
|     "from nltk.stem import PorterStemmer\n", | ||||
|     "from nltk.tokenize import sent_tokenize, word_tokenize\n", | ||||
|     "from nltk.corpus import wordnet\n", | ||||
|     "import math" | ||||
|     "import math\n", | ||||
|     "import pprint\n", | ||||
|     "\n", | ||||
|     "pp=pprint.PrettyPrinter(indent=4)" | ||||
|    ] | ||||
|   }, | ||||
|   { | ||||
| @ -270,11 +273,11 @@ | ||||
|   }, | ||||
|   { | ||||
|    "cell_type": "code", | ||||
|    "execution_count": 106, | ||||
|    "execution_count": 130, | ||||
|    "metadata": {}, | ||||
|    "outputs": [], | ||||
|    "source": [ | ||||
|     "result = evaluate_sentence(\"car soccer surf\")" | ||||
|     "result = evaluate_sentence(\"I like playing soccer\")" | ||||
|    ] | ||||
|   }, | ||||
|   { | ||||
| @ -286,7 +289,7 @@ | ||||
|   }, | ||||
|   { | ||||
|    "cell_type": "code", | ||||
|    "execution_count": 107, | ||||
|    "execution_count": 131, | ||||
|    "metadata": {}, | ||||
|    "outputs": [], | ||||
|    "source": [ | ||||
| @ -304,7 +307,7 @@ | ||||
|   }, | ||||
|   { | ||||
|    "cell_type": "code", | ||||
|    "execution_count": 108, | ||||
|    "execution_count": 139, | ||||
|    "metadata": {}, | ||||
|    "outputs": [], | ||||
|    "source": [ | ||||
| @ -312,33 +315,86 @@ | ||||
|     "max_val = np.argsort([-np.max(x) for x in result])\n", | ||||
|     "avg =  np.argsort([-np.mean(x) for x in result])\n", | ||||
|     "\n", | ||||
|     "t = 0.7\n", | ||||
|     "threshold = np.argsort([-len(np.where(x>t)[0]) for x in result])\n" | ||||
|     "t = 0.9\n", | ||||
|     "threshold = np.argsort([-len(np.where(x>t)[0]) / (x.shape[0] * x.shape[1]) for x in result])\n" | ||||
|    ] | ||||
|   }, | ||||
|   { | ||||
|    "cell_type": "code", | ||||
|    "execution_count": 109, | ||||
|    "execution_count": 156, | ||||
|    "metadata": {}, | ||||
|    "outputs": [], | ||||
|    "source": [ | ||||
|     "def print_best_results(sorted_indices, n=10):\n", | ||||
|     "    pp.pprint([lookup[x] + \" -- \" + str(table.iloc[x]['description']) for x in sorted_indices[:10]])\n", | ||||
|     "    pp.pprint([result[x] for x in sorted_indices[:10]])" | ||||
|    ] | ||||
|   }, | ||||
|   { | ||||
|    "cell_type": "code", | ||||
|    "execution_count": 157, | ||||
|    "metadata": {}, | ||||
|    "outputs": [ | ||||
|     { | ||||
|      "data": { | ||||
|       "text/markdown": [ | ||||
|        "# 🏉⚾🎳🔥🏐🎱💏🧾🚗🚘" | ||||
|       ], | ||||
|       "text/plain": [ | ||||
|        "<IPython.core.display.Markdown object>" | ||||
|       ] | ||||
|      }, | ||||
|      "metadata": {}, | ||||
|      "output_type": "display_data" | ||||
|      "name": "stdout", | ||||
|      "output_type": "stream", | ||||
|      "text": [ | ||||
|       "[   '⚽ -- SOCCER BALL',\n", | ||||
|       "    '🏉 -- RUGBY FOOTBALL',\n", | ||||
|       "    '🏈 -- AMERICAN FOOTBALL',\n", | ||||
|       "    '🎴 -- FLOWER PLAYING CARDS',\n", | ||||
|       "    '🃏 -- PLAYING CARD BLACK JOKER',\n", | ||||
|       "    '🇮 -- REGIONAL INDICATOR SYMBOL LETTER I',\n", | ||||
|       "    '\\U0001f91f -- I LOVE YOU HAND SIGN',\n", | ||||
|       "    '📧 -- E-MAIL SYMBOL',\n", | ||||
|       "    '📭 -- OPEN MAILBOX WITH LOWERED FLAG',\n", | ||||
|       "    '📥 -- INBOX TRAY']\n", | ||||
|       "[   array([[0.25      , 0.28571429, 0.58333333, 1.        ],\n", | ||||
|       "       [0.26666667, 0.10526316, 0.1       , 0.1       ]]),\n", | ||||
|       "    array([[0.25      , 0.28571429, 0.58333333, 0.84615385],\n", | ||||
|       "       [0.26666667, 0.3       , 0.60869565, 0.96      ]]),\n", | ||||
|       "    array([[0.33333333, 0.125     , 0.11764706, 0.11764706],\n", | ||||
|       "       [0.26666667, 0.3       , 0.60869565, 0.96      ]]),\n", | ||||
|       "    array([[0.23529412, 0.0952381 , 0.09090909, 0.09090909],\n", | ||||
|       "       [0.25      , 0.47619048, 1.        , 0.58333333],\n", | ||||
|       "       [0.30769231, 0.33333333, 0.57142857, 0.7       ]]),\n", | ||||
|       "    array([[0.25      , 0.47619048, 1.        , 0.58333333],\n", | ||||
|       "       [0.53333333, 0.22222222, 0.21052632, 0.21052632],\n", | ||||
|       "       [0.30769231, 0.22222222, 0.21052632, 0.21052632],\n", | ||||
|       "       [0.28571429, 0.11111111, 0.10526316, 0.10526316]]),\n", | ||||
|       "    array([[0.        , 0.        , 0.        , 0.        ],\n", | ||||
|       "       [0.33333333, 0.23529412, 0.22222222, 0.22222222],\n", | ||||
|       "       [0.4       , 0.26666667, 0.25      , 0.25      ],\n", | ||||
|       "       [0.30769231, 0.22222222, 0.21052632, 0.21052632],\n", | ||||
|       "       [1.        , 0.26666667, 0.25      , 0.25      ]]),\n", | ||||
|       "    array([[1.        , 0.26666667, 0.25      , 0.25      ],\n", | ||||
|       "       [0.33333333, 0.23529412, 0.22222222, 0.22222222],\n", | ||||
|       "       [0.        , 0.        , 0.        , 0.        ],\n", | ||||
|       "       [0.28571429, 0.11111111, 0.10526316, 0.10526316],\n", | ||||
|       "       [0.33333333, 0.23529412, 0.22222222, 0.22222222]]),\n", | ||||
|       "    array([[0.28571429, 0.31578947, 0.45454545, 0.5       ],\n", | ||||
|       "       [0.4       , 0.26666667, 0.25      , 0.25      ]]),\n", | ||||
|       "    array([[0.30769231, 0.11764706, 0.11111111, 0.11111111],\n", | ||||
|       "       [0.26666667, 0.10526316, 0.1       , 0.1       ],\n", | ||||
|       "       [0.        , 0.        , 0.        , 0.        ],\n", | ||||
|       "       [0.22222222, 0.14285714, 0.13333333, 0.13333333],\n", | ||||
|       "       [0.26666667, 0.10526316, 0.1       , 0.1       ]]),\n", | ||||
|       "    array([[0.        , 0.        , 0.        , 0.        ],\n", | ||||
|       "       [0.26666667, 0.10526316, 0.1       , 0.1       ]])]\n" | ||||
|      ] | ||||
|     } | ||||
|    ], | ||||
|    "source": [ | ||||
|     "def print_best_results(sorted_indices, n=10):\n", | ||||
|     "    print([lookup[x] + \" -- \" + table.iloc[]])" | ||||
|     "print_best_results(threshold)" | ||||
|    ] | ||||
|   }, | ||||
|   { | ||||
|    "cell_type": "code", | ||||
|    "execution_count": null, | ||||
|    "metadata": {}, | ||||
|    "outputs": [], | ||||
|    "source": [] | ||||
|   }, | ||||
|   { | ||||
|    "cell_type": "code", | ||||
|    "execution_count": null, | ||||
|  | ||||
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