machinelearning.py

from sklearn.datasets import make_classification
from sklearn.linear_model import SGDClassifier
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score, log_loss
import numpy as np
import time
import logging

# ---------------- LOGGER ----------------
logging.basicConfig(
    level=logging.INFO,
    format='[%(levelname)s] %(message)s'
)

logger = logging.getLogger(__name__)

start = time.time()

logger.info("Corriendo machinelearning.py...")

logger.info("Generando dataset...")

# ---------------- DATA ----------------
X, y = make_classification(
    n_samples=100000,
    n_features=20,
    n_informative=15,
    n_classes=2,
    random_state=42
)

X_train, X_val, y_train, y_val = train_test_split(
    X, y, test_size=0.2, random_state=42
)

logger.info("Inicializando modelo...")

model = SGDClassifier(
    loss="log_loss",
    max_iter=1000,
    warm_start=True,
    random_state=42
)

epochs = 30

logger.info("Iniciando entrenamiento...")

# ---------------- TRAIN LOOP ----------------
for epoch in range(epochs):

    model.fit(X_train, y_train)

    # ---------------- TRAIN METRICS ----------------
    train_pred = model.predict(X_train)
    train_acc = accuracy_score(y_train, train_pred)

    train_proba = model.predict_proba(X_train)
    train_loss = log_loss(y_train, train_proba)

    # ---------------- VAL METRICS ----------------
    val_pred = model.predict(X_val)
    val_acc = accuracy_score(y_val, val_pred)

    val_proba = model.predict_proba(X_val)
    val_loss = log_loss(y_val, val_proba)

    logger.info(
        f"Época {epoch+1}/{epochs} | "
        f"Train acc: {train_acc:.4f} | loss: {train_loss:.4f} || "
        f"Val acc: {val_acc:.4f} | loss: {val_loss:.4f}"
    )

    time.sleep(0.2)

# ---------------- FINAL ----------------
logger.info("Evaluación final...")

preds = model.predict(X_val)
acc = accuracy_score(y_val, preds)

logger.info(f"Accuracy final: {acc:.4f}")

end = time.time()

logger.info(f"Tiempo total: {round(end - start, 2)} segundos")
logger.info("Proceso terminado")