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대회 19

CIBMTR - Equity in post-HCT Survival Predictions #4 GPU LightGBM Baseline [CV 681 LB 685)

This is an annotation of this kernel:https://www.kaggle.com/code/cdeotte/gpu-lightgbm-baseline-cv-681-lb-685 GPU LightGBM Baseline - [CV 681 LB 685]Explore and run machine learning code with Kaggle Notebooks | Using data from CIBMTR - Equity in post-HCT Survival Predictionswww.kaggle.comGPU LightGBM BaselineIn this notebook, we present a GPU LightGBM baseline. In this notebook, compared to my pr..

대회 2025.02.03

CIBMTR - Equity in post-HCT Survival Predictions #3 Understanding Survival Analysis - 2

Annotation of modeling & SHAP part of this kernel: Understanding Survival AnalysisExplore and run machine learning code with Kaggle Notebooks | Using data from CIBMTR - Equity in post-HCT Survival Predictionswww.kaggle.comXGBoost Model for SurvivalWe will now use an XGBoost model with Optuna to find the ideal hyperparameters. This model will be used to submit predictions.This XGBoost model imple..

대회 2025.02.01

CIBMTR - Equity in post-HCT Survival Predictions #2 Understanding Survival Analysis - 1

Annotation of this kernel: https://www.kaggle.com/code/benjenkins96/understanding-survival-analysis Understanding Survival AnalysisExplore and run machine learning code with Kaggle Notebooks | Using data from CIBMTR - Equity in post-HCT Survival Predictionswww.kaggle.comInitial EDA# Check the distribution of the target variablesplt.figure(figsize=(10, 5))sns.countplot(data=train, x='efs', palett..

대회 2025.02.01

CZII - CryoET Object Identification #4 Making synthetic data for Baseline YOLO11 Solution

This is an annotation of code that produces datasets for YOLO solution with additional data(synthetic data)Trained weights: https://www.kaggle.com/datasets/sersasj/czii-yolo-l-trained-with-synthetic-data/dataCode: https://www.kaggle.com/code/sersasj/czii-making-datasets-for-yolo-synthetic-data#CZII:-Creating-Datasets-for-YOLO-with-Additional-DataCZII making datasets for YOLO + synthetic dataMod..

대회 2025.01.28
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