This is a re-implementation of @veryfid's wonderful Tesla Coil indicator to leverage basic Machine Learning Algorithms to help classify coil crossovers. The original Tesla Coil indicator requires extensive training and practice for the user to develop adequate intuition to interpret coil crossovers. The goal for this version is to help the user understand the underlying logic of the Tesla Coil indicator and provide a more intuitive way to interpret the indicator. The signals should be interpreted as suggestions rather than as a hard-coded set of rules.
NOTE: Please do NOT trade off the signals blindly. Always try to use your own intuition for understanding the coils and check for confluence with other indicators before initiating a trade.
NOTE: Please do NOT trade off the signals blindly. Always try to use your own intuition for understanding the coils and check for confluence with other indicators before initiating a trade.
Versionsinformation:
- Enhancements for settings interface
- Better default settings
Versionsinformation:
- Removed unused setting
Versionsinformation:
- Add Maximum Entropy Spectral Analysis (MESA) line for dominant cycle identification; can be used as added confluence to screen ML Signals
- Remove unused confluence logic
Versionsinformation:
- Use built-in constant for pi
Versionsinformation:
- Simplify dominant cycle measurement
- Add toggles for ML Signals and MESA Baseline
❤️ Patreon w/ Lorentzian Beta: www.patreon.com/jdehorty
🎥 Lorentzian Classification Tutorial: youtu.be/AdINVvnJfX4
🤖 Discord w/ Deep Forecast: discord.gg/djXT5sAPfQ
⏩ LinkedIn: www.linkedin.com/in/justin-dehorty
🎥 Lorentzian Classification Tutorial: youtu.be/AdINVvnJfX4
🤖 Discord w/ Deep Forecast: discord.gg/djXT5sAPfQ
⏩ LinkedIn: www.linkedin.com/in/justin-dehorty