torch-two-sample - Friedman-Rafsky Test: Compare two population based on a multivariate generalization of the Runstest. Explanation, Application Power and Sample Size Calculations pwrss - Statistical Power and Sample Size Calculation Tools (R package), Tutorial with t-test Interim Analyses / Sequent...
@visualize_profiling def complex_calculation(numbers): return [num*2 for num in numbers if num % 2 == 0] complex_calculation(range(1000000)) 这里,SnakeViz将性能数据导出为Chrome浏览器可查看的文件,便于交互式探索函数调用时分布,直观识别瓶颈所在。 通过这些步骤,性能剖析装饰器不仅提供了快速、无侵入式...
output: ret int Indicates whether the calculation is successful. outStr str SHA256 value. """ def read_chunks(fhdl): """read chunks""" chunk = fhdl.read(8096) while chunk: yield chunk chunk = fhdl.read(8096) else: fhdl.seek(0) if not isinstance(file_path, str): logging.error(...
Can use either depth-based metrics or density-based metrics for calculation of outlier scores. Supports sample/observation weights, either as sampling importance or as distribution density measurement. Supports user-provided column sample weights. ...
Enable binary metrics calculation azureml-train-automl-runtime Add TCNForecaster support to model test runs. Update the model test predictions.csv output format. The output columns now include the original target values and the features, which were passed in to the test run. This can...
of code after the Python formula in the previous step, in the same Excel cell, or you can enter it in a new Python in Excel cell in your workbook. If you choose to enter it in a new cell, make sure to follow the row-major calculation order rules and enter it after the...
Highly recommended for Intel CPUs to achieve up to 2x faster "fast" periodogram calculation. gsl (default) - enables GNU scientific library support. You need a compatible version of GSL installed on your system. It is used as an optional optimization algorithm for BazinFit and VillarFit. ...
63 mu_indices = sample(range(n), extra_neurons)64 mu_new = x[mu_indices, :]65 mu = vstack((mu_clusters, mu_new))66 67 return mu 68 69 def _calculate_sigmas(self):70 neurons = self.neurons 71 mu = self.mu 72 73 sigmas = zeros((neurons, ...
# sgd([w1, w2, b], lr, batch_size) z = Calculation(X, w1, b) # 隐藏层输入 a = Activation(z) # 隐藏层输出 a_y = softmax(a, w2) # 输出层输出 S_2 = (a_y - y) S_1 = Activation_(z) * torch.matmul(S_2, w2.T) # 第l层误差项 δ(l) = f'(z(l)).*(w(l+1...
FileSize this_is_a_script 120 this_is_my_first_file 105 Performance tips Reduce the plugin's input dataset to the minimum amount required (columns/rows). Use filters on the source dataset, when possible, with Kusto's query language. To do a calculation on a subset of the source columns...