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Econometrics with Machine

Felix Chan - Nama Orang; László Mátyás - Nama Orang;

On the face of it, econometrics and machine learning share a common goal: to build a predictive model, for a variable of interest, using explanatory variables (or features). However, the two fields have developed in parallel, thus creating two different cultures. Econometrics set out to build probabilistic models designed to describe economic phenomena, while machine learning uses algorithms capable of learning from their mistakes, generally for classification purposes (sounds, images, etc.). Yet in recent years, learning models have been found to be more effective than traditional econometric methods (the price to pay being lower explanatory power) and are, above all, capable of handling much larger datasets. Given this, econometricians need to understand what the two cultures are, what differentiates them and, above all, what they have in common in order to draw on tools developed by the statistical learning community with a view to incorporating them into econometric models.


Ketersediaan
#
eBook (eBook) 657.7 FEL e
14000302
Tersedia
Informasi Detail
Judul Seri
-
No. Panggil
657.7 FEL e
Penerbit
Australia : Springer Nature Switzerland., 2022
Deskripsi Fisik
385 hlm
Bahasa
English
ISBN/ISSN
9783031151491
Klasifikasi
657.7
Tipe Isi
text
Tipe Media
-
Tipe Pembawa
-
Edisi
Vol. 53
Subjek
Umum
ebook
Info Detail Spesifik
-
Pernyataan Tanggungjawab
Felix Chan
Versi lain/terkait

Tidak tersedia versi lain

Lampiran Berkas
  • Econometrics with Machine
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