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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: model/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