diff --git a/doc/requirements.md b/doc/requirements.md
index b44e43b..47746cb 100644
--- a/doc/requirements.md
+++ b/doc/requirements.md
@@ -45,11 +45,19 @@ E --> F[预测服务]
 classification_algorithms = [
     "逻辑回归",
     "支持向量机(SVM)",
+    "支持向量数据描述(SVDD)",
+    "决策树",
     "随机森林",
     "XGBoost",
+    "AdaBoost",
+    "CatBoost",
     "LightGBM",
     "朴素贝叶斯",
+    "高斯朴素贝叶斯",
+    "多项式朴素贝叶斯",
+    "伯努利朴素贝叶斯",
     "K近邻(KNN)",
+    "加权K近邻",
     "多层感知机(MLP)",
     "梯度提升决策树(GBDT)",
     "深度神经网络(DNN)"
@@ -60,12 +68,16 @@ classification_algorithms = [
 ```python
 regression_algorithms = [
     "线性回归",
+    "多项式回归",
     "岭回归",
     "Lasso回归",
-    "弹性网络",
+    "弹性网络回归",
     "支持向量回归(SVR)",
+    "决策树回归",
     "随机森林回归",
     "XGBoost回归",
+    "AdaBoost回归",
+    "CatBoost回归",
     "LightGBM回归",
     "多层感知机回归"
 ]
@@ -75,6 +87,9 @@ regression_algorithms = [
 ```python
 clustering_algorithms = [
     "K均值(K-Means)",
+    "K-Means++",
+    "层次化K-Means",
+    "模糊C均值(FCM)",
     "层次聚类",
     "DBSCAN",
     "高斯混合模型(GMM)",
@@ -96,8 +111,15 @@ timeseries_algorithms = [
 ```python
 dimensionality_reduction = [
     "主成分分析(PCA)",
+    "独立主成分分析(ICA)",
     "线性判别分析(LDA)", 
     "t-SNE",
+    "局部线性嵌入(LLE)",
+    "自编码(AE)",
+    "奇异值分解(SVD)",
+    "多维缩放(MDS)",
+    "非负矩阵分解(NMF)"
+    "自组织映射(SOM)",
     "UMAP"
 ]
 ```
@@ -107,6 +129,10 @@ dimensionality_reduction = [
 recommendation_algorithms = [
     "深度协同过滤(DeepCF)",
     "神经矩阵分解(NeuMF)",
+    "KNN",
+    "朴素贝叶斯",
+    "K-Means",
+    "非负矩阵分解(NMF)"
     "Wide & Deep"
 ]
 ```