误差平方和(Sum of Squared Errors, SSE),也称为残差平方和,是统计学和机器学习中常用的一个概念。它表示观测值与预测值(或拟合值)之间差异的平方和。误差平方和是衡量模型拟合优度的一个重要指标,值越小表示模型拟合得越好。 2. 给出计算误差平方和的公式 误差平方和的公式为: [ SSE = \sum_{i=1}^{n...
sum(squared_error) return J Example #5Source File: test_bayestar.py From dustmaps with GNU General Public License v2.0 6 votes def test_bounds(self): """ Test that out-of-bounds coordinates return NaN reddening, and that in-bounds coordinates do not return NaN reddening. """ for mode...
3.AN ERROR ESTIMATE OF BEM TO BIHARMONIC EQUATION求解平面双调和方程边界元法的误差分析 4.Minimax Estimation of Parameter of a Class Distributions under the Squared Log Error and MLINEX Loss Functions对数误差平方损失函数和MLINEX损失函数下一类分布族参数的Minimax估计 5.The error analysis of GPS surve...
baseline =0.0sampled_loss = torch.sum((binary_samples - p0)**2)# probs, draw_array = get_all_probs(e_b, d)# losses_array = get_losses_from_draw_array(draw_array, p0)## cat_rv = Categorical(probs)# indx = cat_rv.sample()# binary_samples = draw_array[indx]# sampled_loss ...
defalcation- the sum of money that is misappropriated red ink,red,loss- the amount by which the cost of a business exceeds its revenue; "the company operated at a loss last year"; "the company operated in the red last year" assets- anything of material value or usefulness that is owne...
defsolveCardinalityObjective(prices,error):""" Solves the problem for i=1:n max: x[i] subject to: ||Rx - y||_2 <= error, x>=0, sum(x)==1 which is a lower bound approximation to the problem with objective: card(x) R is a number of time periods by number of assets matrix ...
The cross-validated predictive performance was then evaluated by minimizing the root mean squared error (RMSE) or maximizing the Pearson correlation to rank the predictive capability of individual pathways. When this analysis was applied to the CTD2 dataset24,“REACTOME_POST_TRANSLATIONAL_PROTEIN_...
This depends on your loss function. In many circumstances it makes sense to give more weight to points further away from the mean--that is, being off by 10 is more than twice as bad as being off by 5. In such cases RMSE is a more appropriate measure of error. ...
:param nMaxIter: Maximum number of iterations. :type nMaxIter: int. :param th: Threshold applied to RMS error between prior and current cluster centers. :type th: float. :return 2D matrix with computed cluster centers with dimensions> nDim x nCenter. ...
policy_loss = - tf.reduce_sum( tf.reduce_sum( tf.multiply( log_pi, self.a ), reduction_indices=1 ) * self.td + entropy * entropy_beta ) # R (input for value) self.r = tf.placeholder("float", [None]) # value loss (output) # (Learning rate for Critic is half of Actor's...