bootstrap=False, n_jobs=-1, random_state=1) # fit_predict 函数 训练和预测一起 可以得到模型是否异常的判断,-1为异常,1为正常 df['label'] = iforest.fit_predict(X) # 预测 decision_function 可以得出 异常评分 df['scores'] = ifor...
and from negativeinfinity to 0 if lambd is negative.No. 5 :Help on method gammavariate in module random:gammavariate(alpha, beta) method of random.Random instanceGamma distribution. Not the gamma function!Conditions on the parameters are alpha > 0 and beta > 0.The probability distribution funct...
random.expovariate(lambd) 指数分布 random.gammavariate(alpha, beta) 伽马分布 random.gauss(mu, sigma) 高斯分布 random.lognormvariate(mu, sigma) 对数正态分布 random.normalvariate(mu, sigma) 正态分布 random.vonmisesvariate(mu, kappa) 卡帕分布 random.paretovariate(alpha) 帕累托分布 random.weibullvaria...
class Random(_random.Random): """Random number generator base class used by bound module functions. Used to instantiate instances of Random to get generators that don't share state. Especially useful for multi-threaded programs, creating a different instance of Random for each thread, and using ...
numpy.random模块中另一个有用的函数是np.random.choice,它可以从向量中抽样元素。假设我们有一个由 30 名学生组成的班级,我们想随机选择其中的四个。首先,我们生成虚构的学生名单:students = ['student_' + str(i) for i in range(1,31)] 现在,可以使用np.random.choice来随机选择其中四个:...
random.triangular(low,high,mode) 返回一个low <= N <=high的三角形分布的随机数。参数mode指明众数出现位置。 random.betavariate(alpha,beta) β分布。返回的结果在0~1之间 random.expovariate(lambd) 指数分布 random.gammavariate(alpha,beta) 伽马分布 ...
I[ij]是一种指标函数,如果用户i具有额定项目j,则该函数为 1;否则为零。 相对于用户参数和项目资料,成本最小化。 通常,这种优化会导致过拟合,因此,将用户的规范和物料配置文件用作成本函数的正则化,如下所示: [外链图片转存失败,源站可能有防盗链机制,建议将图片保存下来直接上传(img-x4hprobb-1681654125430)...
() classes = breast_cancer_data.target_names.tolist() # split data into train and test from sklearn.model_selection import train_test_split x_train, x_test, y_train, y_test = train_test_split(breast_cancer_data.data, breast_cancer_data.target, test_size=0.2, random_state=0) clf ...
also known as infantile or early-life failures. Weibull distributions with β close to or equal to 1 have a fairly constant failure rate, indicative of useful life or random failures. Weibull distributions with β > 1 have a failure rate that increases with time, also known as wear-out fail...
random.randrange(stop)# 返回range(0,stop)之间的一个整数 random.randrange(start, stop[, step])# 返回range[start,stop)之间的一个整数,可加step,跟range(0,10,2)类似 random.randint(a, b)# 返回range[a,b]之间的一个整数,等价于然的range(a,b+1) ...