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YANS2019ハッカソンのデータ / コード

Python 0.71% Jupyter Notebook 99.29%

yans_hakathon_2019's Introduction

YANS ハッカソン 2019 (Kaggleハッカソンコース)

Kaggle ハッカソン

ベースラインモデル

    1. SVM + TF-IDF feature
    1. MLP + Glove vectors (sum of word vectors)

https://colab.research.google.com/drive/1sCOOtH9PRtCBK6Z2LgXxeOhuNpED1m9H

質問は YANS Slackで @Motoki Sato まで。

データセット

使った訓練データ サイズ ペナルティー付きスコア データ
訓練データ 全体 222,074ペア Accuracy - 5.0 % train_222070.csv
訓練データ 中 100,000ペア Accuracy - 2.0 % train_100000.csv
訓練データ 小 10,000ペア Accuracy train_10000.csv
$ head train.csv
"question1","question2","is_duplicate"
"How do the people of Delhi feel about their chief minister?","How do people in Delhi feel about the AAP?","0"
"How long does chloroform knock you out for?","How long is a person knocked out for?","0"

※ train_10000.csv の中のデータはtrain_100000.csvは包含しています。(ソート順がランダムになっています)

開発データ (dev)

テストデータ

2日目の18:00に配布予定 http://sato-motoki.com/yans/hackathon2019/dataset/test.csv

test.csvの形式 (5000ペア)

$ head test.csv
"question1","question2"
"Which are hogehoge?","How strong is hogehoge?"

提出していただくファイル : predict.csv 5000行に 0, 1が予測されているファイルを提出してください。 (@Motoki Satoまで DMで送ってください) 締め切り : 3日目 9:30まで

$ head predict.csv
0
1
0
1

yans_hakathon_2019's People

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