Interestingly "gioza" and "gyoza" as factors come out with opposite signs. I guess that provides a heuristic confidence interval for the weights.
Machine Learning and Ketosis
11–20 of 309 posts
Re: Machine Learning and Ketosis
#12This is all good if your goal is weight loss. However weight loss doesn't necessarily means higher fitness. Glycogen is fundamental if you do sports, and exercise is a major ingredient in getting fit. If I read correctly, exercise was not a big part of your experiment, how would you suggest modifying the experiment to accommodate one's exercising needs? On a side note, I reached a similar conclusion on the role of "c…
Re: Machine Learning and Ketosis
#13This is all good if your goal is weight loss. However weight loss doesn't necessarily means higher fitness. Glycogen is fundamental if you do sports, and exercise is a major ingredient in getting fit. If I read correctly, exercise was not a big part of your experiment, how would you suggest modifying the experiment to accommodate one's exercising needs? On a side note, I reached a similar conclusion on the role of "c…
If anything, I would question how healthy ketosis is, long term... But I'm pretty sure it's way healthier than any processed-food diet typical in the west...
Re: Machine Learning and Ketosis
#14Re: Machine Learning and Ketosis
#15Three things I'm really curious about:
- How significant are the estimates of lifestyle factors? Do you have p-values? If you bootstrap resample, how much do the rankings change at the extremes?
- How much cognitive overhead did it impose to collect the data for this? Did you put a lot of effort into designing the tags beforehand or making sure you weighed yourself at a consistent time?
- It looks like the predicted delta from going from a "nosleep" day to a "sleep" days is about 1.4 pounds (sleep coef minus nosleep coef). That seems fishy, or at least like it will stop working fairly soon because you can't actually lose 1.4 pounds/day sustainably. Is it possible there's something weird going on with the data or those variables don't have the obvious meanings?
Re: Machine Learning and Ketosis
#16The article was very impressive. I liked the graphs and presentation.
Re: Machine Learning and Ketosis
#17This is all good if your goal is weight loss. However weight loss doesn't necessarily means higher fitness. Glycogen is fundamental if you do sports, and exercise is a major ingredient in getting fit. If I read correctly, exercise was not a big part of your experiment, how would you suggest modifying the experiment to accommodate one's exercising needs? On a side note, I reached a similar conclusion on the role of "c…
How did people fight off lions before there was sugar and pasta?
Re: Machine Learning and Ketosis
#18This matches my experience of weight loss using high fat diet. I started it after hearing Sarah Hallberg's Tedx talk. https://www.youtube.com/watch?v=da1vvigy5tQ&feature=youtu.be For a vegetarian, starting and continuing the high fat low carb diet is difficult. Are there any resources for more vegetarian recipes for high fat low carb food? The article was very impressive. I liked the graphs and presentation.
http://eatingacademy.com/personal/actually-eat-part-iii-circ...
http://eatingacademy.com/nutrition/what-i-actually-eat
http://eatingacademy.com/personal/what-i-actually-eat-part-i...
Re: Machine Learning and Ketosis
#19I'm wrapping up week 5 tomorrow and I'm down 25lbs (~14% of my body weight)! They promise 2-5lbs of fat loss a week. I generally drop around a pound a day, but I'll get stuck a few days here and there. This method really works for me.
The best part is how fast you lose it. When I did South Beach years ago, it took me months to hit my goal. I have 14lbs left now and I should be able to hit my goal by Labor Day.
Give it a try.