OpenStreetMap
CENTSOARER's Notes
Notes submitted or commented on by CENTSOARER
| Id | Creator | Description | Created at | Last changed | |
|---|---|---|---|---|---|
| 4939953 | Carlos Martin Noriega | tortillería El Maicito #OsmAnd |
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| 4939955 | Carlos Martin Noriega | Car Wash Autolavado #OsmAnd |
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| 4939954 | Carlos Martin Noriega | tienda six #OsmAnd |
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| 4939956 | Carlos Martin Noriega | Biblioteca Roger Enrique Pacheco Campos #OsmAnd |
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| 4940183 | Local |
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| 4940188 | Majoyoyo | Tienda física |
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| 4940262 | geo:20.658784,-98.022444?z=19osm.org/?#map=19/20.658784/-98.022444&layers=CNGhttps://globalgoals.org/goals/17-partnerships-for-the-goals/https://globalgoals.org/partner/ixhuatlanmadero.gob.mx/ https://ཱྀ࿌྿༡༣ོིོོིིོེིེིེོེེིེེིིེོོིིེོེིིེུུུཡིེིཡིེིེེིིེེོེིིེིེིིོེིུུུཆུཆོོེིོོིོིིོིོིིོིིོིིོོོིེེིེེིེེིེུུུུུུུུམ༇࿋ཱྀ࿏ྐདྷ༔༾དྷྭྠ༇ྔྮྃཀྵྦྰྐ༷ྵྐ྄ྂ྅ཿ࿋.doc.samsungmobile.com/SM-A045M/TCE/doc.html-20/8-2025༢༥༥༠_=_=_°▪︎☆•1°•☆▪︎|=+`°•▪︎☆▪︎★▪︎◆▪︎•°`https://wiki.openstreetmap.org/wiki/Tag:_=https://www.volunteerhq.org/ca/https://doc.samsungmobile.com/SM-A045M/TCE/doc.html-20/8-2025_=_=_°▪︎☆•1°•☆https://faq.whatsapp.com/227626810186044?lg=es&lc=USNO ME CULPES: https://music.youtube.com/watch?v=lgavF-Ko4Xg&feature=sharehttps://faq.whatsapp.com/1848531392146538/?helpref=uf_sharehttps://faq.whatsapp.com/1217634902127718/?helpref=uf_sharehttps://faq.whatsapp.com/523679699550284/?helpref=uf_sharehttps://faq.whatsapp.com/849367647393371/?helpref=uf_sharehttps://faq.whatsapp.com/764072925284841/?helpref=uf_share**IMPLEMENTACIÓN COMPLETA DEL CÓDIGO** **Código completo con funciones desarrolladas:** ```python import pandas as pd from sklearn.model_selection import train_test_split from sklearn.linear_model import LinearRegression from sklearn.metrics import mean_squared_error Cargar datos de la región datos = pd.read_csv('datos_region.csv') Establecer objetivos objetivo_emisiones = 0.2 # reducir emisiones en 20% objetivo_empleo = 0.1 # aumentar empleo en 10% objetivo_seguridad = 0.05 # mejorar seguridad en 5% Análisis de datos X = datos.drop(['emisiones', 'empleo', 'seguridad'], axis=1) y = datos['emisiones'] X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42) Modelo de regresión lineal modelo = LinearRegression() modelo.fit(X_train, y_train) predicciones = modelo.predict(X_test) Evaluación del modelo mse = mean_squared_error(y_test, predicciones) print(f'Error cuadrático medio: {mse:.https://globalgoals.org/partner/ixhuatlanmadero.gob.mx/https://doc.samsungmobile.com/S |
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| 4940389 | Jose jj | Ki |
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| 4908912 | BPM805 | "wrong location..proper location already on the map"
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| 4908914 | BPM805 | "there is no snorkelling here on land"
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