From e2ec6d10669e207abfd10180e81ff040f40ce38d Mon Sep 17 00:00:00 2001
From: xiaochaoroulalala <1206174039@qq.com>
Date: Thu, 23 Nov 2023 22:27:40 +0800
Subject: [PATCH] 1.3

---
 readme.md           | 4 ++++
 yugou_theoryBest.py | 2 +-
 2 files changed, 5 insertions(+), 1 deletion(-)

diff --git a/readme.md b/readme.md
index 744fee6..941e5a8 100644
--- a/readme.md
+++ b/readme.md
@@ -27,3 +27,7 @@
 元学习器这里采用毛南设计好的adaboost分类器，通过将第一层基础模型的预测结果作为新的特征矩阵进行训练。
 
 融合模型最终输出的预测结果就是元学习器输出的结果。
+
+效果图：
+
+![image-20231123222727368](C:\Users\Lenovo\AppData\Roaming\Typora\typora-user-images\image-20231123222727368.png)
diff --git a/yugou_theoryBest.py b/yugou_theoryBest.py
index e2ab2c2..e24c2c8 100644
--- a/yugou_theoryBest.py
+++ b/yugou_theoryBest.py
@@ -124,7 +124,7 @@
 # 元模型
 meta_model = AdaBoostClassifier(base_estimator=base_classifier, n_estimators=50, learning_rate=0.1, random_state=0)
 # 划分数据集
-X_train_base, X_stack, y_train_base, y_stack = train_test_split(X_train, y_train, test_size=0.2, random_state=0)
+X_train_base, X_stack, y_train_base, y_stack = train_test_split(X_train, y_train, test_size=0.3, random_state=0)
 # 使用基础模型在一部分训练集上训练
 mlp_model.fit(X_train_base, y_train_base)
 logit_model.fit(X_train_base, y_train_base)