95 lines
1.8 KiB
TypeScript
95 lines
1.8 KiB
TypeScript
// 分类算法
|
||
export const classifierAlgorithms = [
|
||
{
|
||
label: 'logistic_regression（逻辑回归）',
|
||
value: 'logistic_regression',
|
||
},
|
||
{
|
||
label: 'decision_tree（决策树）',
|
||
value: 'decision_tree',
|
||
},
|
||
{
|
||
label: 'random_forest（随机森林）',
|
||
value: 'random_forest',
|
||
},
|
||
{
|
||
label: 'SVM（支持向量机）',
|
||
value: 'SVM',
|
||
},
|
||
{
|
||
label: 'naive_bayes（朴素贝叶斯）',
|
||
value: 'naive_bayes',
|
||
},
|
||
{
|
||
label: 'GBM（梯度提升树）',
|
||
value: 'GBM',
|
||
},
|
||
];
|
||
|
||
// 回归算法
|
||
export const regressorAlgorithms = [
|
||
{
|
||
label: 'bayesian_ridge（岭回归）',
|
||
value: 'bayesian_ridge',
|
||
},
|
||
{
|
||
label: 'ARD_regression（自动相关性确定回归）',
|
||
value: 'ARD_regression',
|
||
},
|
||
{
|
||
label: 'gaussian_process（高斯回归）',
|
||
value: 'gaussian_process',
|
||
},
|
||
];
|
||
|
||
// 框架类型
|
||
export enum FrameworkType {
|
||
Sklearn = 'sklearn',
|
||
Keras = 'keras',
|
||
Pytorch = 'pytorch',
|
||
}
|
||
|
||
// 框架类型选项
|
||
export const frameworkTypeOptions = [
|
||
{
|
||
label: FrameworkType.Sklearn,
|
||
value: FrameworkType.Sklearn,
|
||
},
|
||
{
|
||
label: FrameworkType.Keras,
|
||
value: FrameworkType.Keras,
|
||
},
|
||
{
|
||
label: FrameworkType.Pytorch,
|
||
value: FrameworkType.Pytorch,
|
||
},
|
||
];
|
||
|
||
// 查询策略
|
||
export const queryStrategies = [
|
||
{
|
||
label: 'uncertainty_sampling',
|
||
value: 'uncertainty_sampling',
|
||
},
|
||
{
|
||
label: 'uncertainty_batch_sampling',
|
||
value: 'uncertainty_batch_sampling',
|
||
},
|
||
{
|
||
label: 'max_std_sampling',
|
||
value: 'max_std_sampling',
|
||
},
|
||
{
|
||
label: 'expected_improvement',
|
||
value: 'expected_improvement',
|
||
},
|
||
{
|
||
label: 'upper_confidence_bound',
|
||
value: 'upper_confidence_bound',
|
||
},
|
||
{
|
||
label: 'probability_of_improvement',
|
||
value: 'probability_of_improvement',
|
||
},
|
||
];
|