Daesoo Lee's Blog

AUC (Area Under the Curve) [1] developers.google.com/machine-learning/crash-course/classification/roc-and-auc?hl=ko The area under the ROC (receiver operating characteristic) curve. The ROC curve consists of TPR (True Positive Rate) and FPR (False Positive Rate) : $$ TPR = \frac{TP}{TP + FN} $$ $$ FPR = \frac{FP}{FP + TN} $$ The ROC curve can be drawn by adjusting a classification threshold from..

Fourier Series Explained [1] BRILLIANT, "Fourier Series" (link) [2] White Whale, "푸리에 급수(Fourier Series) 수식 예제" (link) Fourier Series used in N-BEATS (i.e., NN-based Fourier Series) B. Oreshkin et al., 2019, "N-BEATS: Neural basis expansion analysis for interpretable time series forecasting" (link)

The most popular/common functions are: scipy.signal.resample scipy.signal.resample_poly from scipy import signal x = np.linspace(0, 10, 20, endpoint=False) y = np.cos(-x**2/6.0) f_fft = signal.resample(y, 100) f_poly = signal.resample_poly(y, 100, 20, padtype='line') # same as "signal.resample_poly(y, 5, 1, padtype='line')" xnew = np.linspace(0, 10, 100, endpoint=False) import matplotlib.pyplot ..

superuser.com/questions/1214467/formatting-list-labels-in-microsoft-powerpoint-independently-of-the-text-that-fo