Topic: data-splitting Goto Github
Some thing interesting about data-splitting
Some thing interesting about data-splitting
data-splitting,This project focuses on cleaning and analyzing a loan application dataset to gain insights into the factors influencing loan defaults. Through systematic data cleaning, visualization, and merging with previous application data, it provides a robust foundation for further predictive modeling.
User: aarryasutar
data-splitting,splitting image dataset into train, val, test sets
User: aravinda89
data-splitting,Python Preprocessing for Sales Project Notebook
User: dimas263
data-splitting,Source code for the article "Accelerating neural network training by data splitting".
User: intersog-developer
data-splitting,Focus on selecting datasets suitable for a machine learning experiment, with an emphasis on data cleaning, encoding, and transformation steps necessary to prepare the data.
User: jesschannn
data-splitting,As Tensorflow Kennard-Stone algorithmin uses euclidean distances, the need for an adaptation arrises when dealing with a big vector space that has unknown correlations between its variables, it may improve a lot neural networks performance.
User: jvtupinamba
data-splitting,A basic Python script to split a .dat file into individual sample files.
User: katiebristol
data-splitting,Predicting company bankruptcy using various machine learning models. The dataset is sourced from Kaggle: Company Bankruptcy Prediction.
User: krisssix
Home Page: https://www.kaggle.com/datasets/fedesoriano/company-bankruptcy-prediction
data-splitting,Analyzed customer churn using transaction data. Built ML model to predict lapses. Dataset includes customer status, collection/redemption info, and program tenure. Delivered business presentation outlining modeling approach, findings, and churn reduction strategies.
User: lefteris-souflas
data-splitting,Utilizing Apache Spark & PySpark to analyze a movie dataset. Tasks include data exploration, identifying top-rated movies, training a linear regression model, and experimenting with Airflow.
User: lefteris-souflas
data-splitting,In this project, I have used logistic regression, a supervised machine learning algorithm, to predict whether a person has diabetes or not based on various features such as age, blood pressure, glucose level, body mass index, etc. I have used Python and popular libraries such as Pandas, Scikit-Learn, and Matplotlib to perfom model building
User: madhubala11
Home Page: https://www.kaggle.com/code/johncubides/diabetesregresion-logostica
data-splitting,A sample model for predicting the systolic level of an individual by providing the age,cholesterol and blood pressure
User: muhireighor
data-splitting,Final project program DBA mitra Ruangguru X Studi Independen Bersertifikat Kampus Merdeka batch 2
User: nabilahsharfina
data-splitting,Comparative Analysis of Data Protection Mechanisms in Public Clouds
User: nicolas-bolouri
data-splitting,Data-Splitter is a Python script designed to split a large CSV file containing data into three different formats: JSON, a database table, and another CSV file. The script ensures a random distribution of data across the three output formats based on custom-defined ratios.
User: omardbaa
data-splitting,ML model for Crop Detection
User: sahilsunda
data-splitting,A Python toolkit for file processing, text cleaning and data splitting. 文件处理,文本清洗和数据划分的python工具包。
User: sharejing
data-splitting,MoleculeNet benchmark dataset & MolMapNet dataset
User: shenwanxiang
data-splitting,As Tensorflow Kennard-Stone algorithmin uses euclidean distances, the need for an adaptation arrises when dealing with a big vector space that has unknown correlations between its variables, it may improve a lot neural networks performance.
Organization: uerj-livia
data-splitting,Apply DUPLEX data split to the given dataset and return training and test datasets. REF: Snee, R. D. (1977). Validation of regression models: methods and examples. Technometrics, 19(4), 415-428.
User: yuerongz
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