疯狂python讲义-第四章的笔记【未结题】 这个章节有些内容略过了;太简单了; 这个用sublime text不行;input()方法不能用; 使用IDLE可以进行操作; 4.2.7pass语句 没有else if ; 而是elif 要注意涂鸦的地方;见下图哦 4.3断言 断言是对一个bool表达式进行断言;若为True,则继续执行;否则引发断言错误;不用缩进;
outlier-detection anomaly anomaly-detection outlier Updated Feb 9, 2024 Python petropouloumaria / NMAoutlier Star 6 Code Issues Pull requests Detecting Outliers in Network Meta-Analysis outlier mahalanobis-distance network-meta-analysis outlier-detection-measures influence-measures Updated Feb 10, ...
Code sample LocalOutlierAnalysis example 1 (Python window) The following Python window script demonstrates how to use the LocalOutlierAnalysis tool. # LocalOutlierAnalysis of homicides in a metropolitan area import arcpy arcpy.env.workspace = r"C:\STPM" arcpy.LocalOutlierAnalysis_stpm("Homicides.nc...
Code sample OptimizedOutlierAnalysis example 1 (Python window) The following Python window script demonstrates how to use the OptimizedOutlierAnalysis function. import arcpy arcpy.env.workspace = r"C:\OOA" arcpy.stats.OptimizedOutlierAnalysis("911Count.shp", "911OptimizedOutlier.shp", "#"...
Chapter 5 - Outlier Analysis Segment 9 - Multivariate analysis for outlier detection import pandas as pd import matplotlib.pyplot as plt from pylab im
Python for Data Science - Multivariate analysis for outlier detection,Chapter5-OutlierAnalysisSegment9-Multivariateanalysisforoutlierdetectionimportpandasaspdimportmatplotlib.pyplotaspltfrompylabim
Python 3.6+ combo>=0.1.3 joblib numpy>=1.19 numba>=0.51 scipy>=1.5.1 scikit_learn>=0.20.0 six statsmodels Optional Dependencies (see details below): combo (optional, required for models/combination.py and FeatureBagging) keras/tensorflow (optional, required for AutoEncoder, and other deep lear...
Exemple de code Cluster and Outlier Analysis with Rendering Example (Python Window) The following Python Window script demonstrates how to use the Cluster and Outlier Analysis with Rendering tool. import arcpy arcpy.env.workspace = "c:/data/911calls" arcpy.ClustersOutliersRendered_stats("911...
Python output=Fig. 4.30 Let's also look at the box plot of “Petroleum_Engineer_Age,”“Petroleum_Engineer_Income (K$),” and “Spending_Habits (From 1 to 100)”. Make sure to place each box plot line of code shown below independently, otherwise, the box plots will overlay. Sign in...
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