Rekayasa fitur

Memenangi Kompetisi Kaggle dengan Python

Yauhen Babakhin

Kaggle Grandmaster

Alur kerja solusi

alur kerja solusi

Tahap pemodelan

komponen tahap pemodelan

Tahap pemodelan

komponen tahap pemodelan

Tahap pemodelan

komponen tahap pemodelan

Rekayasa fitur

skema rekayasa fitur

Rekayasa fitur

skema rekayasa fitur

Jenis fitur

Numerik
Kategorikal
Tanggal-waktu
Koordinat
Teks
Gambar

Membuat fitur

# Concatenate the train and test data
data = pd.concat([train, test])

# Create new features for the data DataFrame...

# Get the train and test back
train = data[data.id.isin(train.id)]
test = data[data.id.isin(test.id)]

Fitur aritmetika

# Two sigma connect competition
two_sigma.head(1)

      id     bathrooms  bedrooms price interest_level
0     10     1.5        3        3000  medium

# Arithmetical features
two_sigma['price_per_bedroom'] = two_sigma.price / two_sigma.bedrooms
two_sigma['rooms_number'] = two_sigma.bedrooms + two_sigma.bathrooms

Fitur tanggal-waktu

# Demand forecasting challenge
dem.head(1)

          id           date store  item  sales
0     100000     2017-12-01     1     1     19

# Convert date to the datetime object
dem['date'] = pd.to_datetime(dem['date'])

Fitur tanggal-waktu

# Year features
dem['year'] = dem['date'].dt.year

# Month features
dem['month'] = dem['date'].dt.month

# Week features
dem['week'] = dem['date'].dt.weekofyear

# Day features
dem['dayofyear'] = dem['date'].dt.dayofyear
dem['dayofmonth'] = dem['date'].dt.day
dem['dayofweek'] = dem['date'].dt.dayofweek

date           year  month   week
2017-12-01     2017     12     48
2017-12-02     2017     12     48
2017-12-03     2017     12     48
2017-12-04     2017     12     49

date      dayofyear  dayofmonth dayofweek
2017-12-01  335      1          4
2017-12-02  336      2          5
2017-12-03  337      3          6
2017-12-04  338      4          0

Ayo berlatih!

Memenangi Kompetisi Kaggle dengan Python