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Tiresias_MLP_Altitude-w2-3-4-p1-v1
bermejo4/Tiresias_MLP_Altitude-w2-3-4-p1-v1
Tiresias_MLP_Altitude-w2-3-4-p1-v1 is a machine learning model from bermejo4. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for keras. The card lists the license as apache-2.0.
Model registered in MLflow. Flavor detected: keras. Export date: 2025-08-03 11:00:36 UTC.
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At a glance
- Library
- keras
- License
- apache-2.0
- Access
- Public
- Created
- Aug 3, 2025
- Updated
- Aug 3, 2025
- SHA
- 779b2b20
Datasets
Model card
From the Hugging Face model README
Model card for MLP_102030_W_2-3-4_PAST_1_Altitude version 1
Overview
Model registered in MLflow. Flavor detected: keras. Export date: 2025-08-03 11:00:36 UTC.
Metrics
- mae_real: 0.477288
- rmse_real: 0.898253
Model inputs / shape
- Input shape (approximate): (None, 707)
Scalers
- scaler_X: used to transform features before prediction (if present).
- scaler_y: used to inverse-transform the model output (if present).
Usage example
from tensorflow.keras.models import load_model
import joblib
import numpy as np
# Cargar
model = load_model('model') # si es Keras SavedModel
scaler_X = joblib.load('scaler_X.joblib') # si existe
scaler_y = joblib.load('scaler_y.joblib') # si existe
# Predecir
# X_raw = ... # tu array de features sin escalar
X_scaled = scaler_X.transform(X_raw)
y_pred_scaled = model.predict(X_scaled)
y_pred = scaler_y.inverse_transform(y_pred_scaled)
Notes
- Asegúrate de que las versiones de TensorFlow / scikit-learn sean compatibles.
- Library
- keras
- License
- apache-2.0
- Languages
- es, en
- Created
- Aug 3, 2025
- Updated
- Aug 3, 2025