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我是机器学习的初学者。这只是一个简单的问题，LinearRegression()中的coef帴代表什么？我知道它代表的是系数，但我不明白这些值，高的和正的系数意味着更强的关系吗？在
而且，如果coef_u值是指数型的，这是否意味着我的线性回归是错误的？在array([-3.12840684e+02, -1.01279891e+13, -1.42682874e+13, -1.42682874e+13,
-1.42682873e+13, -1.42682873e+13, -1.23057091e+04, -6.08730443e+02,
-2.25836847e+12, -2.25836846e+12, -2.25836846e+12, -2.25836846e+12,
-2.25836845e+12, -2.25836846e+12, -2.25836846e+12, -2.25836847e+12,
-2.25836849e+12, 5.41669310e+11, 5.41669341e+11, 5.41669325e+11,
2.47680574e+12, 5.41669172e+11, 5.41669322e+11, 5.41669336e+11,
5.41669320e+11, -1.92388659e+12, -1.92388658e+12, -1.92388659e+12,
-1.92388654e+12, -1.43004842e+12, -1.92388655e+12, -1.92388658e+12,
-1.92388665e+12, -1.92388657e+12, -1.92388658e+12, -1.92388653e+12,
-1.92388658e+12, -1.92388660e+12, -1.92388658e+12, -1.92388660e+12,
-9.83609518e+11, -9.83609497e+11, -9.83609551e+11, -9.83609529e+11,
-1.47744767e+12, -9.83609560e+11, -9.83609506e+11, -9.83609465e+11,
-9.83609519e+11, -9.83609455e+11, -9.83609513e+11, -9.83609555e+11,
-9.83609535e+11, -9.83609497e+11, -9.83609511e+11, -9.83609514e+11,
-1.54590339e+13, -1.54590339e+13, -1.54590339e+13, -1.54590339e+13,
-1.30678844e+12, -1.30678843e+12, -1.30678843e+12, -1.30678847e+12,
-1.30678844e+12, -1.62361585e+13, -1.62361585e+13, -1.62361585e+13,
-1.62361585e+13, -1.62361586e+13, -1.62361585e+13, 5.88718912e+12,
5.88718906e+12, 5.88718908e+12, 5.88718907e+12, -5.88718905e+12,
-5.88718905e+12, -5.88718906e+12, -5.88718904e+12, 3.45085841e+11,
3.45085830e+11, 3.45085861e+11, 3.45085814e+11, 3.45085829e+11,
3.45085830e+11, 3.11126022e+12, 3.11126021e+12, 3.11126021e+12,
1.13335966e+07, 3.11126021e+12, -7.58191433e+11, -7.58191424e+11,
3.04834491e+03, 3.74262207e+03, -1.19176646e+04, -1.16855749e+04,
2.00192065e+03, 3.75148918e+12, 3.75148916e+12, 3.75148918e+12,
3.75148928e+12, 2.24187815e+13, 2.24187815e+13, 2.24187815e+13,
2.24187815e+13, 6.26624305e+04, 1.61187017e+04, 2.00000527e+04,
-3.10534619e+03, 2.39790901e+04, -7.55683101e+12, -7.55683096e+12,
-7.55683096e+12, -7.55683096e+12, -7.55683097e+12, -7.55683097e+12,
2.32335100e+13, 2.32335100e+13, 2.32335100e+13, -1.15363807e+13,
-1.15363808e+13, -1.15363807e+13, -1.15363807e+13, -1.15363807e+13,
2.70555822e+12, 2.70555822e+12, 2.70555823e+12, -3.19955267e+11,
-3.19955228e+11, -3.19955165e+11, -3.19955294e+11, -3.19955247e+11,
-3.19955264e+11, -3.19955255e+11, -3.19955270e+11, -3.19955263e+11,
-4.86759426e+12, -4.86759423e+12, -4.86759425e+12, -4.86759428e+12,
-4.86759425e+12, -4.86759427e+12])
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