## Evaluation Metric
The evaluation metric for this competition is [Accuracy](https://en.wikipedia.org/wiki/Accuracy_and_precision). The accuracy, commonly used in binary classification, accuracy is calculated as:
Accuracy=(TP+TN)/(P+N)
where TP is true positive samples, TN is true negative samples, P and N represent positive samples and negative samples, respectively. 

## Benchmark
The benchmark result is from a simple MLP model, model detail will be updated later. The input of the network is the pseudorange residual, CN0, and elevation angle, output is the probability of the LOS and NLOS

## Submission Format

**For every GPS Time and Every Satellite in the dataset**, submission files should contain two columns: `ID` and `Predict`. `ID` follows the same sequence with the testing dataset, and within each GPS Time, the satellite sequence should also be the same as that in the testing set. Every `Prediction` is an int value, either 1 or 0, where 1 means LOS, 0 means NLOS. 


The file should contain a header and have the following format:
```
ID,Predict
0,1
1,0
2,1
3,0
4,0
5,1
6,0
7,1
8,0
9,0
10,1
11,0
12,1
13,0
```