
kaggle_course
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kaggle_course
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Machine Learning Explainability(1)
PI_kaggleMachine Learning Explainability(1)Why Are These Insights Valuableexample:!!!Permutation Importance code:PI方法不受量纲影响Why Are These Insights ValuableThese insights have many uses, includingDebuggingInforming feature engineeringDirecting future原创 2021-01-29 17:22:30 · 213 阅读 · 0 评论 -
kaggle_course_Interactive_Maps(3)交互式html
Interactive_Maps 3导包one tip1.simplest 的 map2.map+点3.map+聚集起来的点4.map+根据数量多少变化颜色的点5.map+热力图6.map+区域密度显示图Execrise:1.地震和板块的边界2.日本人口密度分布3.人口密度和地震强度导包import pandas as pdimport geopandas as gpdimport mathimport foliumfrom folium import Choropleth, Circle,原创 2021-01-16 00:39:50 · 302 阅读 · 0 评论 -
kaggle_courses_geospatial-analysis(2)
coordinate reference system (CRS)这个有点没看懂(what is the meaning of that?)kaggle_courses_geospatial-analysis 2IntroductionTips计算面积regions.geometry.area(.geometry.area)将dataframe格式的文件转化为GeoDataFrame看一下是否有这两个大陆在这个world['continent']中计算某个地区的面积(以南美South America.原创 2021-01-15 16:48:08 · 191 阅读 · 0 评论