# transconductance_cc

**Repository Path**: alphagw/transconductance_cc

## Basic Information

- **Project Name**: transconductance_cc
- **Description**: 跨到性能机器学习预测模型
- **Primary Language**: Python
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 1
- **Forks**: 0
- **Created**: 2024-06-20
- **Last Updated**: 2024-09-06

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Transconductance_cc

### Introduction
Transconductance value of MxAyO(P)z.

Developed based on [ALKEMIE](https://alkemie.cloud) and [MatterAI](https://alkemie.cloud).

Developed by [Guanjie Wang](https://alkemine.cn/gjwang) and Team of ChenChen

### Install
pip install matfleet>=0.0.9
pip install transconductance_cc


### README
#### 1. 新建输入数据文件名为：check.xlsx
**输入数据文件说明：**
- 前7列为特征列
- 最后一列tc为跨到性能

| mN       | mMeltT  | mColumn  | mCovaR  | mNsVal | mNpVal | A         | tc      |
|----------|---------|----------|---------|--------|--------|-----------|---------|
| 0.47561  | 0.401537| 0.555556 | 0.437018| 1      | 0      | 0.043478  | 1.62108 |
| 0.695122 | 0.396557| 0.055556 | 0.8509  | 0.66667| 0      | 0.304348  | 1.57259 |
| 0.317073 | 0.461314| 0.383333 | 0.488432| 1      | 0      | 0.130435  | 1.61811 |
| 0.195122 | 0.316117| 0.777778 | 0.329049| 1      | 0.2    | 0.826087  | 1.57593 |
| 0.139024 | 0.359159| 0.888889 | 0.318766| 1      | 0.6    | 0.130435  | 1.59    |
| 0.097561 | 0.205437| 0.555556 | 0.372751| 1      | 0.2    | 0.130185  | 1.5     |
| 0.26829  | 0.551783| 0.611111 | 0.352185| 1      | 0.2    | 0.304348  | 1.62    |
| 0.304878 | 0.473139| 0.277778 | 0.51928 | 1      | 0      | 0.130835  | 1.68425 |
| 0.097561 | 0.205437| 0.555556 | 0.372751| 1      | 0.2    | 0.217391  | 1.48    |
| 0.012195 | 1       | 0.611111 | 0.141388| 1      | 0.4    | 0.003478  | 1.46    |
| 0.097561 | 0.205437| 0.555556 | 0.372751| 1      | 0.2    | 0.086957  | 1.48    |
| 0.097561 | 0.307601| 0.27778  | 0.398158| 1      | 0.2    | 0.130135  | 1.45    |
| 0.420732 | 0.330424| 0.805556 | 0.357326| 1      | 0.6    | 0.130435  | 1.5278  |
| 0.317073 | 0.032046| 0.555556 | 0.377892| 1      | 0.2    | 0.043478  | 1.46426 |


#### 2. 运行一下命令进行跨到性能模型测试:
```
# 运行以下命令，进行3次测试，获得测试精度
tctest check.xlsx -b 3

# 运行以下命令，进行5次测试，获得测试精度，并返回模型预测值
tctest check.xlsx -b 5 -d 1
```

#### Developers
[Guanjie Wang](https://alkemine.cn/gjwang), gjwang@buaa.edu.cn