Eylem Seç
Performance Enhancement of Logistic Regression for Big Data on Spark
Başlık:
Performance Enhancement of Logistic Regression for Big Data on Spark
Yazar:
Wang, Mengyao, author.
ISBN:
9780438012608
Yazar Ek Girişi:
Fiziksel Tanımlama:
1 electronic resource (65 pages)
Genel Not:
Source: Masters Abstracts International, Volume: 57-06M(E).
Advisors: Baijian Yang Committee members: John A. Springer; Tonglin Zhang.
Özet:
This research proposes a new fitting algorithm of logistic regression on IRWLS that utilizes the procedure of scanning data row-by-row and has the ability to acquire an exact result with only a few iterations. Furthermore, this research also realizes the distributed parallelization of the proposed method on Spark and conducts various experiments to manifest its memory-wise advantage over the traditional methods such as Spark MLlib package. The results show that the proposed method can provide an exact result rather than an approximated one within 5 or 6 iterations; achieve a satisfying accuracy for flight delay prediction within 1 or 2 iterations; has a better potential for parallelization and a better performance than MLlib with a 3-4x faster speed without full optimizations; and its performance is not undermined by an increasing data memory ratio.
Notlar:
School code: 0183
Tüzel Kişi Ek Girişi:
Mevcut:*
Yer Numarası | Demirbaş Numarası | Shelf Location | Lokasyon / Statüsü / İade Tarihi |
---|---|---|---|
XX(691304.1) | 691304-1001 | Proquest E-Tez Koleksiyonu | Arıyor... |
On Order
Liste seç
Bunu varsayılan liste yap.
Öğeler başarıyla eklendi
Öğeler eklenirken hata oldu. Lütfen tekrar deneyiniz.
:
Select An Item
Data usage warning: You will receive one text message for each title you selected.
Standard text messaging rates apply.