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as 01-17-2025 4:00pm EST

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Polyrizon Ltd is a clinical development stage biotech company specializing in the development of nasal gels to provide preventative treatment to protect against a wide cross-section of viruses, including certain variants of COVID-19 that are also considered to cause more infections and spread faster than the original strain of the virus (the CDC expects that additional variants of the virus will continue to occur), influenza, allergens, and other toxins. Its technology platforms are Capture & Contain and Trap & Target.

More About Our PLRZ ML Model...

What kind of parameters do you use to train PLRZ stocks ML model?

To train our stocks PLRZ ML model, we use historical data with over 25 parameters, including volume indicators, volatility indicators, momentum indicators, trend indicators, and other metrics.

How often do you update PLRZ ML model?

We update our ML model either weekly or biweekly, depending on the market capitalization of the stocks, using TensorFlow, typically over the weekend.

Why is the accuracy of your PLRZ model low?

Unfortunately, our current data provider offers limited historical data, which impacts the accuracy of our ML model. However, as we continue to gather more data over time and add more indicators, we expect the accuracy of our model to improve.

How can I provide and share more data with you to increase your ML model accuracy?

We would greatly appreciate your contribution. Please send an email to [email protected]

Do you offer an ML model for shorter time periods, such as 5 minutes or 15 minutes?

Yes, we offer it for strategy purposes only, with intervals: 1 minute, 2 minutes, 5 minutes, 15 minutes, and 30 minutes etc.

Can I rely on your ML model to make financial decisions regarding buying or selling stocks, or is it only intended for learning purposes?

Our ML model is primarily designed for educational purposes and is not intended to provide financial advice. We strongly recommend consulting with a financial advisor before making any buying or selling decisions.

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