mirror of
https://github.com/jung-geun/PSO.git
synced 2025-12-19 20:44:39 +09:00
74 lines
1.4 KiB
Python
74 lines
1.4 KiB
Python
import gc
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import os
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import sys
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from sklearn.datasets import load_iris
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from sklearn.model_selection import train_test_split
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from tensorflow import keras
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from tensorflow.keras import layers
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from tensorflow.keras.models import Sequential
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from pso import optimizer
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os.environ["TF_CPP_MIN_LOG_LEVEL"] = "2"
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def make_model():
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model = Sequential()
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model.add(layers.Dense(10, activation="relu", input_shape=(4,)))
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model.add(layers.Dense(10, activation="relu"))
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model.add(layers.Dense(3, activation="softmax"))
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return model
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def load_data():
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iris = load_iris()
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x = iris.data
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y = iris.target
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y = keras.utils.to_categorical(y, 3)
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x_train, x_test, y_train, y_test = train_test_split(
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x, y, test_size=0.2, shuffle=True, stratify=y
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)
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return x_train, x_test, y_train, y_test
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model = make_model()
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x_train, x_test, y_train, y_test = load_data()
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pso_iris = optimizer(
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model=model,
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loss="categorical_crossentropy",
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n_particles=100,
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c0=0.5,
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c1=0.3,
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w_min=0.1,
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w_max=0.9,
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negative_swarm=0,
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mutation_swarm=0.1,
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convergence_reset=True,
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convergence_reset_patience=10,
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convergence_reset_monitor="loss",
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convergence_reset_min_delta=0.001,
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)
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best_score = pso_iris.fit(
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x_train,
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y_train,
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epochs=500,
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save_info=True,
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log=2,
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log_name="iris",
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renewal="loss",
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check_point=25,
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validate_data=(x_test, y_test),
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)
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gc.collect()
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print("Done!")
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sys.exit(0)
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