Sklearn中回归不准确系数的套索回归

时间:2015-11-28 04:54:33

标签: python scikit-learn linear-regression

我试图使用sklearn和Lasso回归进行一些分析,但我得到了一些奇怪的结果。我试图缩小问题范围,但问题似乎是我不了解sklearn试图做什么。例如,在下面的代码中,我预计 public void deal() { dealButton.setEnabled(false); noDealButton.setEnabled(false); String message = "You have chosen to accept the banker's offer of " + currency.format(bankerOffer) + " \nBut was it a good deal?\nIf we open your case we reveal"; String message2 = ""; for(int i = 0; i < unshuffledAmounts.size(); i++) { if(unshuffledAmounts.get(i).equals(yourCaseAmount)) { yourCaseNumber = i; } } if(bankerOffer > yourCaseAmount) { message2 = "You made a good deal"; } else { message2 = "Too bad, you made a bad deal"; } 的5次幂系数为2.或者至少接近它。但是,无论我做什么,我都会在16左右获得价值。

关于我错过/做错的任何想法?

x

$$\alpha$$ vs C5

0 个答案:

没有答案