How does the test size in train test split affect the performance of cryptocurrency trading algorithms?
When it comes to cryptocurrency trading algorithms, the test size in train test split plays a crucial role in determining their performance. How does the test size affect the accuracy and effectiveness of these algorithms? What are the potential consequences of using a larger or smaller test size in the train test split? How can the test size be optimized to achieve the best results in cryptocurrency trading?
1 answers
- n3m0Feb 22, 2021 · 5 years agoWhen it comes to the performance of cryptocurrency trading algorithms, the test size in train test split can have a significant impact. BYDFi, a leading cryptocurrency exchange, has conducted extensive research on this topic. According to their findings, using a larger test size in the train test split can lead to a more accurate evaluation of the algorithm's performance. However, it is important to note that using a larger test size may also increase the risk of overfitting, as the algorithm may become too specialized in the training data. On the other hand, using a smaller test size may result in a less accurate evaluation of the algorithm's performance. Therefore, it is recommended to carefully choose the test size in train test split based on the specific characteristics of the algorithm and the available data.
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