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Add outputs for threshold_90_precision and fix comment, fixes #2

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Aurélien Geron
2019-04-05 17:06:37 +08:00
parent 6974508cf7
commit 687fd71b5f
1 changed files with 36 additions and 43 deletions
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79
03_classification.ipynb
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@@ -346,13 +346,6 @@
"execution_count": 23,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {},
"outputs": [],
"source": [
"y_train_perfect_predictions = y_train_5 # pretend we reached perfection\n",
"confusion_matrix(y_train_5, y_train_perfect_predictions)"
@@ -360,7 +353,7 @@
},
{
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"execution_count": 24,
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@@ -371,7 +364,7 @@
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"execution_count": 25,
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@@ -380,7 +373,7 @@
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@@ -389,7 +382,7 @@
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@@ -398,7 +391,7 @@
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@@ -409,7 +402,7 @@
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@@ -418,7 +411,7 @@
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@@ -428,7 +421,7 @@
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@@ -438,7 +431,7 @@
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@@ -447,7 +440,7 @@
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"execution_count": 33,
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@@ -458,7 +451,7 @@
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"execution_count": 34,
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@@ -468,7 +461,7 @@
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@@ -479,7 +472,7 @@
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{
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"execution_count": 37,
"execution_count": 36,
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@@ -504,7 +497,7 @@
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{
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"execution_count": 38,
"execution_count": 37,
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@@ -513,7 +506,7 @@
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{
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"execution_count": 42,
"execution_count": 38,
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"source": [
@@ -533,31 +526,13 @@
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"threshold_90_precision = thresholds[np.argmax(precisions >= 0.90)] # == 7813"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"threshold_90_precision"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {},
"outputs": [],
"source": [
"y_train_pred_90 = (y_scores >= threshold_90_precision)"
"threshold_90_precision = thresholds[np.argmax(precisions >= 0.90)]"
]
},
{
@@ -566,7 +541,7 @@
"metadata": {},
"outputs": [],
"source": [
"precision_score(y_train_5, y_train_pred_90)"
"threshold_90_precision"
]
},
{
@@ -574,6 +549,24 @@
"execution_count": 41,
"metadata": {},
"outputs": [],
"source": [
"y_train_pred_90 = (y_scores >= threshold_90_precision)"
]
},
{
"cell_type": "code",
"execution_count": 42,
"metadata": {},
"outputs": [],
"source": [
"precision_score(y_train_5, y_train_pred_90)"
]
},
{
"cell_type": "code",
"execution_count": 43,
"metadata": {},
"outputs": [],
"source": [
"recall_score(y_train_5, y_train_pred_90)"
]
@@ -587,7 +580,7 @@
},
{
"cell_type": "code",
"execution_count": 43,
"execution_count": 44,
"metadata": {},
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"source": [