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#---设备配置---#
device : cpu
#device: cuda
#---训练配置---#
n_epochs : 150
batch_size : 16
learning_rate : 0.001
nc : 4
use_infer_as_val : true
#data_train: train_val # train: 只用train训练, val做验证, infer做测试; train_val: 用train和val做训练, infer做验证, infer做测试; all: 全部训练, 全部验证, 全部测试( 数据先1/5作为infer, 剩下的再1/5作为val, 剩下的4/5作为训练)
data_train : all
early_stop_patience : 50
gamma : 0.98
step_size : 10
experiments_count : 50
#---训练结果---#
# 日志路径
log_path : results/training.log
# 训练过程统计图路径
train_process_path : results/training_progress.png
# 训练结果统计图路径
train_result_path : results/training_result.png
# 训练模型路径
model_path : results/psychology.pth
# 用于测试的部分数据路径
infer_path : results/infer.xlsx
#---训练原始数据---#
# 训练样本数据路径配置
data_path : data_processed/feature_label_weighted.xlsx
#---样本特征---#
# 标签名称
label_name : 类别
# 特征名称
feature_names :
- "强迫症状数字化"
- "人际关系敏感数字化"
- "抑郁数字化"
- "多因子症状"
- "母亲教养方式数字化"
- "父亲教养方式数字化"
- "自评家庭经济条件数字化"
- "有无心理治疗(咨询)史数字化"
- "学业情况数字化"
- "出勤情况数字化"
# 定义特征权重列表
feature_weights :
- 0.135
- 0.085
- 0.08
- 0.2
- 0.09
- 0.09
- 0.06
- 0.06
- 0.08
- 0.12