aliosmankaya
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Commit
•
5967a0e
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Parent(s):
3ee1a0c
Upload 2 files
Browse files- reg_arr_model_1_dim.ipynb +413 -0
- reg_arr_model_1_dim.joblib +3 -0
reg_arr_model_1_dim.ipynb
ADDED
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "e1bdbd46-1f35-4373-80ec-727f0e26f009",
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"metadata": {},
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"import pandas as pd\n",
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"from sklearn.datasets import load_iris\n",
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"from sklearn.model_selection import train_test_split\n",
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"from sklearn.linear_model import LinearRegression\n",
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"from sklearn.metrics import accuracy_score\n",
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"\n",
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"import warnings\n",
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"warnings.filterwarnings(\"ignore\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "327dafe0-68d4-4200-a889-b03bc97a1057",
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"metadata": {},
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"outputs": [],
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"source": [
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"iris = load_iris()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"id": "5ced7579-bb9f-4a20-abe2-c0c258ef4073",
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"metadata": {},
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"outputs": [],
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"source": [
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"X = iris.data[:, :1]\n",
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"y = iris.target"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"id": "50359601-4b0d-4a94-a1c8-44a833b8f4e5",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"x_train, x_test, y_train, y_test = train_test_split(X, y, test_size=0.1, random_state=42)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"id": "17fc4619-c5c0-4beb-81df-81617b1c7a56",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"(array([[6.3],\n",
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" [6.5],\n",
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" [5.6],\n",
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" [5.7],\n",
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" [6.4]]),\n",
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" array([1, 2, 1, 1, 2]))"
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]
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},
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"execution_count": 5,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"x_train[:5], y_train[:5]"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"id": "510d7a07-7746-4305-96d6-a74bc5a7f144",
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"metadata": {},
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"outputs": [],
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"source": [
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"model = LinearRegression()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"id": "733f81f4-fc25-41a2-8c7d-e6e4abd70143",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"LinearRegression()"
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]
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},
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"execution_count": 7,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"model.fit(x_train, y_train)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"id": "267ed05e-7285-4873-ae8c-2396f986bf31",
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"metadata": {},
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"outputs": [],
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"source": [
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"y_pred = model.predict(x_test)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"id": "0dd6f9d6-89d4-461f-9110-601d44126512",
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"metadata": {},
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"outputs": [
|
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{
|
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"data": {
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"text/plain": [
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+
"array([1.22816565, 0.91925051, 2.46382623, 1.15093687, 1.76876716,\n",
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131 |
+
" 0.68756415, 0.84202172, 1.84599594, 1.30539444, 0.99647929,\n",
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" 1.5370808 , 0.22419143, 0.76479293, 0.30142022, 0.45587779])"
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+
]
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+
},
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+
"execution_count": 9,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"y_pred"
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]
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},
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{
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"cell_type": "code",
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+
"execution_count": 10,
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"id": "6a65cd71-b625-4f31-894d-a4d0403fd1b1",
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"metadata": {},
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"outputs": [
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{
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"data": {
|
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"text/plain": [
|
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"array([1., 1., 2., 1., 2., 1., 1., 2., 1., 1., 2., 0., 1., 0., 0.])"
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]
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},
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"execution_count": 10,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"y_pred = np.round(y_pred)\n",
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"y_pred"
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]
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},
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{
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"cell_type": "code",
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+
"execution_count": 11,
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"id": "ef5d8327-7ee8-43a6-b4f9-0785e8467d23",
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"metadata": {},
|
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+
"outputs": [
|
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+
{
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"data": {
|
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"text/plain": [
|
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"array([1, 0, 2, 1, 1, 0, 1, 2, 1, 1, 2, 0, 0, 0, 0])"
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]
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},
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"execution_count": 11,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"y_test"
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]
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},
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{
|
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"cell_type": "code",
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"execution_count": 12,
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"id": "b28aa4ac-87ab-45a4-b5c8-e7b125895c25",
|
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+
"metadata": {},
|
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+
"outputs": [
|
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+
{
|
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"data": {
|
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"text/plain": [
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"0.7333333333333333"
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]
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},
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"execution_count": 12,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"accuracy_score(y_test, np.round(y_pred))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 13,
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"id": "d5cf8629-f623-4a3e-9400-8d7f6215383e",
|
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"metadata": {},
|
213 |
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"outputs": [],
|
214 |
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"source": [
|
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"from joblib import dump, load"
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]
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},
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{
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"cell_type": "code",
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+
"execution_count": 14,
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+
"id": "caa6d389-b358-4160-a342-215013c5b2d9",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"['reg_arr_model_1_dim.joblib']"
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]
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},
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"execution_count": 14,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
|
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"dump(model, \"reg_arr_model_1_dim.joblib\")"
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]
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},
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{
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"cell_type": "code",
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+
"execution_count": 15,
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+
"id": "f0804a91-46d4-4cec-bd60-bb5f022443bf",
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"metadata": {},
|
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"outputs": [],
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"source": [
|
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"model = load(\"reg_arr_model_1_dim.joblib\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 16,
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"id": "07584f03-f1da-4014-a539-ca0e033a6356",
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"metadata": {},
|
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"outputs": [
|
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+
{
|
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"data": {
|
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"text/plain": [
|
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"array([1.22816565])"
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]
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+
},
|
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+
"execution_count": 16,
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+
"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"model.predict(x_test[:1])"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 17,
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"id": "06cf5cbb-0a96-4501-8fa6-bfc680d8aa20",
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"metadata": {},
|
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"outputs": [],
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"source": [
|
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"import skops.hub_utils as hub_utils"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 18,
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"id": "f4349089-88c9-49d2-8b65-351cabb74fd8",
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"metadata": {},
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"outputs": [
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{
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"data": {
|
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"text/plain": [
|
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"array([[6.1],\n",
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" [5.7],\n",
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" [7.7],\n",
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" [6. ],\n",
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" [6.8],\n",
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" [5.4],\n",
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295 |
+
" [5.6],\n",
|
296 |
+
" [6.9],\n",
|
297 |
+
" [6.2],\n",
|
298 |
+
" [5.8],\n",
|
299 |
+
" [6.5],\n",
|
300 |
+
" [4.8],\n",
|
301 |
+
" [5.5],\n",
|
302 |
+
" [4.9],\n",
|
303 |
+
" [5.1]])"
|
304 |
+
]
|
305 |
+
},
|
306 |
+
"execution_count": 18,
|
307 |
+
"metadata": {},
|
308 |
+
"output_type": "execute_result"
|
309 |
+
}
|
310 |
+
],
|
311 |
+
"source": [
|
312 |
+
"x_test"
|
313 |
+
]
|
314 |
+
},
|
315 |
+
{
|
316 |
+
"cell_type": "code",
|
317 |
+
"execution_count": 19,
|
318 |
+
"id": "a4294f1f-5eeb-460f-a872-ba487a229093",
|
319 |
+
"metadata": {},
|
320 |
+
"outputs": [],
|
321 |
+
"source": [
|
322 |
+
"!rm -rf /Users/macbookpro/MyProjects/dev/dst\n",
|
323 |
+
"!mkdir /Users/macbookpro/MyProjects/dev/dst"
|
324 |
+
]
|
325 |
+
},
|
326 |
+
{
|
327 |
+
"cell_type": "code",
|
328 |
+
"execution_count": 20,
|
329 |
+
"id": "41a49678-1a01-439d-8f92-29f1884e5f79",
|
330 |
+
"metadata": {},
|
331 |
+
"outputs": [],
|
332 |
+
"source": [
|
333 |
+
"hub_utils.init(\n",
|
334 |
+
" model=\"/Users/macbookpro/MyProjects/dev/structured_arr_model.joblib\",\n",
|
335 |
+
" requirements=[\"scikit-learn\", \"numpy\"],\n",
|
336 |
+
" dst=\"/Users/macbookpro/MyProjects/dev/dst\",\n",
|
337 |
+
" task=\"tabular-classification\",\n",
|
338 |
+
" data=x_train[:3]\n",
|
339 |
+
")"
|
340 |
+
]
|
341 |
+
},
|
342 |
+
{
|
343 |
+
"cell_type": "code",
|
344 |
+
"execution_count": 21,
|
345 |
+
"id": "fe1a1620-66e3-4543-a506-1195ac39831e",
|
346 |
+
"metadata": {},
|
347 |
+
"outputs": [],
|
348 |
+
"source": [
|
349 |
+
"from skops.card import metadata_from_config"
|
350 |
+
]
|
351 |
+
},
|
352 |
+
{
|
353 |
+
"cell_type": "code",
|
354 |
+
"execution_count": 22,
|
355 |
+
"id": "9e0a6d81-e1c4-4a75-b510-772eb44e924d",
|
356 |
+
"metadata": {},
|
357 |
+
"outputs": [
|
358 |
+
{
|
359 |
+
"data": {
|
360 |
+
"text/plain": [
|
361 |
+
"library_name: sklearn\n",
|
362 |
+
"tags:\n",
|
363 |
+
"- sklearn\n",
|
364 |
+
"- skops\n",
|
365 |
+
"- tabular-classification\n",
|
366 |
+
"widget:\n",
|
367 |
+
" structuredData:\n",
|
368 |
+
" x0:\n",
|
369 |
+
" - 6.3\n",
|
370 |
+
" - 6.5\n",
|
371 |
+
" - 5.6"
|
372 |
+
]
|
373 |
+
},
|
374 |
+
"execution_count": 22,
|
375 |
+
"metadata": {},
|
376 |
+
"output_type": "execute_result"
|
377 |
+
}
|
378 |
+
],
|
379 |
+
"source": [
|
380 |
+
"metadata_from_config(\"/Users/macbookpro/MyProjects/dev/dst/config.json\")"
|
381 |
+
]
|
382 |
+
},
|
383 |
+
{
|
384 |
+
"cell_type": "code",
|
385 |
+
"execution_count": null,
|
386 |
+
"id": "412fc8e8-ab28-44bf-88be-6cac61c168f1",
|
387 |
+
"metadata": {},
|
388 |
+
"outputs": [],
|
389 |
+
"source": []
|
390 |
+
}
|
391 |
+
],
|
392 |
+
"metadata": {
|
393 |
+
"kernelspec": {
|
394 |
+
"display_name": "Python 3 (ipykernel)",
|
395 |
+
"language": "python",
|
396 |
+
"name": "python3"
|
397 |
+
},
|
398 |
+
"language_info": {
|
399 |
+
"codemirror_mode": {
|
400 |
+
"name": "ipython",
|
401 |
+
"version": 3
|
402 |
+
},
|
403 |
+
"file_extension": ".py",
|
404 |
+
"mimetype": "text/x-python",
|
405 |
+
"name": "python",
|
406 |
+
"nbconvert_exporter": "python",
|
407 |
+
"pygments_lexer": "ipython3",
|
408 |
+
"version": "3.9.15"
|
409 |
+
}
|
410 |
+
},
|
411 |
+
"nbformat": 4,
|
412 |
+
"nbformat_minor": 5
|
413 |
+
}
|
reg_arr_model_1_dim.joblib
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:e5bb34d8b7d267d3f3bd6bcf1a108eb0d2ffdf45e31b773627c776bd08853095
|
3 |
+
size 552
|