ultima versao

create_alloy_model.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [
     {
@@ -39,7 +39,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -114,7 +114,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [
     {
@@ -123,7 +123,7 @@
        "['models/tawos/aloy/model_tawos_aloy_tfidf_linear.joblib']"
       ]
      },
-     "execution_count": 6,
+     "execution_count": 17,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -181,8 +181,8 @@
     "# Extração das features para o TFIDF\n",
     "vectorizer = TfidfVectorizer()\n",
     "X_vec = vectorizer.fit_transform(df[\"context_\"])\n",
-    "\n",
-    "dump(vectorizer, \"models/tawos/aloy/vectorizer_tfidf.joblib\")\n",
+    "dump(vectorizer, \"vectorizer_tfidf.joblib\")\n",
+    "#dump(vectorizer, \"models/tawos/aloy/vectorizer_tfidf.joblib\")\n",
     "\n",
     "df_vec = pd.DataFrame(data = X_vec.toarray(), columns = vectorizer.get_feature_names_out())\n",
     "\n",
@@ -194,37 +194,43 @@
     "\n",
     "model = DummyRegressor(strategy=\"mean\")\n",
     "model.fit(X, y)\n",
-    "dump(model, \"models/tawos/aloy/model_tawos_aloy_mbr.joblib\")\n",
+    "dump(model, \"model_tawos_aloy_mbr.joblib\")\n",
+    "#dump(model, \"models/tawos/aloy/model_tawos_aloy_mbr.joblib\")\n",
     "\n",
     "############ Mediana\n",
     "\n",
     "model = DummyRegressor(strategy=\"median\")\n",
     "model.fit(X, y)\n",
-    "dump(model, \"models/tawos/aloy/model_tawos_aloy_median.joblib\")\n",
+    "dump(model, \"model_tawos_aloy_median.joblib\")\n",
+    "#dump(model, \"models/tawos/aloy/model_tawos_aloy_median.joblib\")\n",
     "\n",
     "########### NEOSP-SVR\n",
     "\n",
     "model = svm.SVR()\n",
     "model.fit(X[X.columns[5:16]], y)\n",
-    "dump(model, \"models/tawos/aloy/model_tawos_aloy_neosp_svr.joblib\")\n",
+    "dump(model, \"model_tawos_aloy_neosp_svr.joblib\")\n",
+    "#dump(model, \"models/tawos/aloy/model_tawos_aloy_neosp_svr.joblib\")\n",
     "\n",
     "########### NEOSP-LR\n",
     "\n",
     "model = LinearRegression()\n",
     "model.fit(X[X.columns[5:16]], y)\n",
-    "dump(model, \"models/tawos/aloy/model_tawos_aloy_neosp_linear.joblib\")\n",
+    "dump(model, \"model_tawos_aloy_neosp_linear.joblib\")\n",
+    "#dump(model, \"models/tawos/aloy/model_tawos_aloy_neosp_linear.joblib\")\n",
     "\n",
     "############ TFIDF-SVM\n",
     "\n",
     "model = svm.SVR()\n",
-    "model.fit(X[X.columns[17:]], y)\n",
-    "dump(model, \"models/tawos/aloy/model_tawos_aloy_tfidf_svr.joblib\")\n",
+    "model.fit(X[X.columns[16:]], y)\n",
+    "dump(model, \"model_tawos_aloy_tfidf_svr.joblib\")\n",
+    "#dump(model, \"models/tawos/aloy/model_tawos_aloy_tfidf_svr.joblib\")\n",
     "\n",
     "############ TFIDF-LR\n",
     "\n",
     "model = LinearRegression()\n",
-    "model.fit(X[X.columns[17:]], y)\n",
-    "dump(model, \"models/tawos/aloy/model_tawos_aloy_tfidf_linear.joblib\")\n"
+    "model.fit(X[X.columns[16:]], y)\n",
+    "dump(model, \"model_tawos_aloy_tfidf_linear.joblib\")\n",
+    "#dump(model, \"models/tawos/aloy/model_tawos_aloy_tfidf_linear.joblib\")\n"
    ]
   },
   {

model_tawos_aloy_tfidf_linear.joblib

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model_tawos_aloy_tfidf_svr.joblib

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models/tawos/aloy/model_tawos_aloy_mbr.joblib

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models/tawos/aloy/model_tawos_aloy_median.joblib

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models/tawos/aloy/model_tawos_aloy_neosp_linear.joblib

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models/tawos/aloy/model_tawos_aloy_neosp_svr.joblib

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models/tawos/aloy/model_tawos_aloy_tfidf_linear.joblib

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models/tawos/aloy/model_tawos_aloy_tfidf_svr.joblib

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models/tawos/aloy/vectorizer_tfidf.joblib

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