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1, Data set description 1. Data set Tabular Playground Series - Feb 2022 | KagglePractice your ML skills on this approachable dataset!https://www.kaggle.com/c/tabular-playground-series-feb-2022/data For this challenge, you will predict bacterial species based on repeated lossy measurements of DNA fragments. The fragment with length of 10 is ...

In recent years, with the expansion of onshore wind turbine assembly sites, wind turbines installed in regions with more abrupt weather changes have been increasingly affected by climate change. When the wind condition changes suddenly, due to the lag of the control system, it is easy to cause the unit to show excessive load and even turn over, ...

Kaggle case: predictive classification of cardiac patients based on a random forest Hello, my name is Peter~ A kaggle case shared today: predictive classification of cardiac patients based on the RandomForest model. The knowledge points involved in this paper mainly include: Data preprocessing and type transformationEstablishment and Interpr ...

catalogue reference material 1. Import package 2. Import data 3. View the first 5 rows of data 4. Transformation of categorical variables into dummy variables (gender) Knowledge point - dummy variable 5. Merge data frame 6. Delete unnecessary columns 7. Count the missing value of each line 8. Visual missing value 9. View and visualiz ...

I've heard that many bosses acquire knowledge from kaggle and process it into their own competition system In July this year, I started to participate in the big data competition. Now there are almost 10 competitions, all of which are structured competitions. Small competitions can still get into the Top ranking, but larger competitions are ...

preface In order to record my learning process, I have roughly sorted out the analysis process. The tool is to use Jupiter notebook, which I prefer, and then export it into md format and send it to csdn to share with you; This is only a simple analysis process, so it is relatively simple. If there is something wrong, I hope you can include it ...

catalogue 1, EDA (Exploratory Data Analysis) 2, Data Preprocessing 3, Feature Engineering 4, Model Selection and Training 5, Model Ensemble 1, EDA (Exploratory Data Analysis) EDA: exploratory analysis of data Purpose: Understand the meaning of each feature;Know which features are useful, which can be used directly, and which can be u ...