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merge prediction optimization

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This commit is contained in:
Carsten 2018-06-26 23:05:27 +02:00
parent 33b1e26a2a
commit cd6167f80a
1 changed files with 32 additions and 22 deletions
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48
Project/Tools/User_Interface.ipynb
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@ -139,7 +139,9 @@
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"#sys.path.append(\"..\")\n",
@ -151,7 +153,9 @@
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"tmp_dict = clf_naive.prepareData()"
@ -167,8 +171,10 @@
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {},
"execution_count": 7,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"def merged_prediction(msg , split = 0.5 , number = 8, target_emojis = top_emojis):\n",
@ -178,10 +184,23 @@
" number_naive = round((1-split)*number)\n",
" \n",
" #predict emojis with the naive approach\n",
" prediction_naive = clf_naive.predict(sentence = msg, lookup= tmp_dict, n = number_naive)\n",
" prediction_naive , prediction_naive_values = clf_naive.predict(sentence = msg, lookup= tmp_dict, n = number_naive)\n",
"\n",
" #filter 0 values\n",
" tmp1 = []\n",
" tmp2 = []\n",
" epsilon = 0.0001\n",
"\n",
" for i in range(len(prediction_naive)):\n",
" if(abs(prediction_naive_values[i]) > epsilon):\n",
" tmp1.append(prediction_naive[i])\n",
" tmp2.append(prediction_naive[i])\n",
"\n",
" prediction_naive = tmp1\n",
" prediction_naive_values = tmp2\n",
" \n",
" if(len(prediction_naive) < number_naive):\n",
" print(\"only few matches\")\n",
" #print(\"only few matches\")\n",
" number_advanced = number - len(prediction_naive)\n",
" \n",
" #print(number, number_advanced, number_naive)\n",
@ -222,8 +241,9 @@
" #p = ed.sentiment_vector_to_emoji(sent,n_results = 8, custom_target_emojis=top_emojis)\n",
" \n",
" #merged prediction\n",
" if(current_message != \"\"):\n",
" p = merged_prediction(msg = current_message, target_emojis=top_emojis)\n",
" \n",
"\n",
" predictions = p\n",
" update_descriptions()"
]
@ -527,13 +547,13 @@
},
{
"cell_type": "code",
"execution_count": 24,
"execution_count": 23,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "9b6fd63901c84db9a5a2d10399053cb3",
"model_id": "3b8a6a311c1e4a1bb2b711d59246577a",
"version_major": 2,
"version_minor": 0
},
@ -543,16 +563,6 @@
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"8 4 4\n",
"8 4 4\n",
"8 4 4\n",
"8 4 4\n"
]
}
],
"source": [