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as 12-18-2024 10:40am EST

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Nasdaq

Tortoise Energy Independence Fund, Inc. is a non-diversified closed-end management investment company. Its primary investment objective to seek a high level of total return with an emphasis on current distributions. The fund invests primarily in equity securities of upstream North American energy companies that engage in the exploration and production of crude oil, condensate, natural gas and natural gas liquids that generally have a presence in North American oil and gas fields, including shale reservoirs.

More About Our NDP ML Model...

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

To train our stocks NDP 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 NDP 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 NDP 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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