小编Cla*_*ark的帖子

我使用 pyGAD Python 库提供的遗传算法实现训练了一组神经网络。到目前为止我编写的代码如下：

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import pygad.gann
import time
import pickle

ret = -1
n_sect = 174
population_size = 500
num_parents_mating = 4 
num_generations = 1000
mutation_percent = 5
parent_selection_type = "rank"
crossover_type = "two_points"
mutation_type = "random"
keep_parents = 1
init_range_low = -2
init_range_high = 5
n_div = 15

data = pd.read_csv("delta_results/sub_delta_{}.csv".format(n_sect), index_col=0)
data.index = pd.to_datetime(data.index)
data = list(data["Delta"])

function_inputs = np.array([data[i:i+n_div][:ret] for i in range(0, len(data), …