From 0310f248403a02fb9ee93c77f2593626459fa997 Mon Sep 17 00:00:00 2001
From: haotian <2421912570@qq.com>
Date: Thu, 10 Apr 2025 10:46:58 +0800
Subject: [PATCH] =?UTF-8?q?=E4=BF=AE=E6=94=B9--=E4=BF=AE=E6=94=B9=E6=96=87?=
 =?UTF-8?q?=E6=A1=A3?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 doc/典型示例新版.md |  2 +-
 doc/接口文档code.md | 80 ++++++++++++++++++++++++++++++---------------
 2 files changed, 55 insertions(+), 27 deletions(-)

diff --git a/doc/典型示例新版.md b/doc/典型示例新版.md
index bd6dbba..b512d97 100644
--- a/doc/典型示例新版.md
+++ b/doc/典型示例新版.md
@@ -107,7 +107,7 @@ NASA Turbofan Engine Degradation Simulation数据集（通常称为C-MAPSS数据
 - 超过55%的变异性未被模型捕获，说明初始模型拟合效果不佳
 
 **参数优化**：
-使用GridSearchCV进行超参数调优，探索以下参数组合（共1296种组合）：
+RandomForestRegressor使用GridSearchCV进行超参数调优，探索以下参数组合（共1296种组合）：
 
 | 参数名称 | 可选值 |
 |----------|--------|
diff --git a/doc/接口文档code.md b/doc/接口文档code.md
index a0798ab..2b9a739 100644
--- a/doc/接口文档code.md
+++ b/doc/接口文档code.md
@@ -136,6 +136,13 @@ Request:
     "input_path": "dataset/dataset_raw/train_FD001.csv",
     "output_dir": "dataset/dataset_processed/",
     "process_methods": [
+        {
+            "method_name": "IsolationForest",
+            "params": {
+                "n_estimators": 100,
+                "max_samples": "auto"
+            }
+        },
         {
             "method_name": "StandardScaler",
             "params": {
@@ -144,12 +151,10 @@ Request:
             }
         }
     ],
-    "feature_methods":[
-    ],
+    "feature_methods": [],
     "split_params": {
-        "train_size": 0.7,
-        "val_size": 0.3
-
+        "train_size": 0.8,
+        "val_size": 0.2
     }
 }
 
@@ -467,14 +472,14 @@ Content-Type: application/json
 
 Request:
 {
-  "train_path": "/home/admin-root/haotian/MLPlatform/dataset/dataset_processed/train_FD001_20250407_174421/train_train_FD001_20250407_174421.csv",
-  "val_path": "/home/admin-root/haotian/MLPlatform/dataset/dataset_processed/train_FD001_20250407_174421/val_train_FD001_20250407_174421.csv",
-  "algorithm": "RandomForestRegressor",
-  "task_type": "regression",
+  "train_path": "dataset/dataset_processed/tpb_20250409_174922/train_tpb_20250409_174922.csv",
+  "val_path": "dataset/dataset_processed/tpb_20250409_174922/val_tpb_20250409_174922.csv",
+  "algorithm": "MLPClassifier",
+  "task_type": "classification",
   "parameters": {
 
   },
-  "experiment_name": "test_FD001_1"
+  "experiment_name": "test_tpb_1"
 }
 
 Response:
@@ -731,29 +736,52 @@ Content-Type: application/json
 
 Request:
 {
-    run_id": "bd3697dc238c4d1587e0f4f319d04448",
+    "data_path": "/home/admin-root/haotian/MLPlatform/dataset/dataset_processed/train_FD001_20250409_105906",
+    "output_dir": null,
+    "experiment_name": "test_FDD001_1",
     "method": "GridSearchCV",
     "parameters": {
-        "max_depth": [3, 5, 7],
-        "n_estimators": [50, 100, 200],
-        "min_samples_split": [2, 5, 10]
+        "param_grid": { //一定要加参数网格
+            "n_estimators": [
+                50,
+                100,
+                200
+            ],
+            "max_depth": [
+                null,
+                10,
+                20,
+                30
+            ]
+
+        },
+        "scoring": "r2" // 评价指标,不同任务选择不同指标.
     },
-    "data_path": "dataset/dataset_processed/test_optimize/train.csv",
-    "output_dir": None,
-    "experiment_name": "测试模型优化方法"
+    "run_id": "ef413c6fd25f4042a793d4c452af3e1b"
 }
 
 Response:
 {
-    "status": "success",
-    "optimization": {
-        
-    "status": "success",
-    "message": "优化任务已执行",
-    "run_id": "903ab190690e496aa74e6aaefac8a7cb", # 新的运行id
-    "optimized_model_id": "bd3697dc238c4d1587e0f4f319d04448" # 被优化模型的运行id
-
-    }
+  "status": "success",
+  "message": "优化任务已执行",
+  "optimization": {
+    "id": "opt_20250410_cbc1d9",
+    "run_id": "2c9d4363e55b4530a6881633ade5f4e3",
+    "experiment_id": "670583721104894053",
+    "task_id": "opt_20250410_cbc1d9",
+    "method": "GridSearchCV",
+    "original_model": "regression",
+    "best_params": { //最佳参数
+      "max_depth": 10,
+      "n_estimators": 200
+    },
+    "best_score": 0.4481105476031095,
+    "cv_results_file": "optimized_models/opt_20250410_cbc1d9/cv_results.csv",
+    "optimized_model_id": "ef413c6fd25f4042a793d4c452af3e1b",
+    "execution_time": "0:01:51.399587",
+    "status": "completed",
+    "timestamp": "2025-04-10T10:20:09.709085"
+  }
 }
 
 Error Response: