Autoresearch + TOTO: Autonomous AI Experiments for Time Series Energy Forecasting | Jd Fiscus
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Autoresearch + TOTO: Autonomous AI Experiments for Time Series Energy Forecasting | Jd Fiscus
Loops, loops and more loops I wanted to build something with Karpathy's #autoresearch concepts. Everything I'm messing with has some variation of Local AI. Granite, Qwen, MiniMax and Nemotron being my recent favorites. I've been thinking alot about time series data and Zachary Gwirtz pointed me at TOTO which has fine-tuning. Alright things are ...
2K views1 month ago
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SOLVED:A second-order autoregressive model for the gas prices is: Dependent variable is: Gas R squared -82.2 % R squared (adjusted) -77.1 % s-0.1498 with 10-3-7 degrees of freedom Variable Coefficient SE(Coeff) t-ratio P-value Intercept 1.28207 0.4644 2.76 0.0281 Lag1?Gas? 1.31432 0.2383 5.51 0.0009 Lag2?Gas? -0.788250 0.2457 -3.21 0.0149 Using values from the table, what is the predicted value for January 2007.
SOLVED:A second-order autoregressive model for the gas prices is: Dependent variable is: Gas R squared -82.2 % R squared (adjusted) -77.1 % s-0.1498 with 10-3-7 degrees of freedom Variable Coefficient SE(Coeff) t-ratio P-value Intercept 1.28207 0.4644 2.76 0.0281 Lag1?Gas? 1.31432 0.2383 5.51 0.0009 Lag2?Gas? -0.788250 0.2457 -3.21 0.0149 Using values from the table, what is the predicted value for January 2007.
numerade.com
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