عنوان

Atış tipi tahminleme probleminde sınıflandırma algoritmalarının karşılaştırılması

شماره

TL58131

زبان متن نوشتاري يا گفتاري و مانند آن

انگلیسی

عنوان اصلي

Atış tipi tahminleme probleminde sınıflandırma algoritmalarının karşılaştırılması

نام عام مواد

[Thesis]

نام نخستين پديدآور

Türkmen, Fatih

نام ساير پديدآوران

Ergenç Bostanoğlu, Belgin

نام ناشر، پخش کننده و غيره

Izmir Institute of Technology (Turkey)

تاریخ نشرو بخش و غیره

2020

متن يادداشت

66 p.

جزئيات پايان نامه و نوع درجه آن

Master's

کسي که مدرک را اعطا کرده

Izmir Institute of Technology (Turkey)

امتياز متن

2020

متن يادداشت

The dramatic increase in the use of IoT devices has been leading to a huge amount of valuable data to be discovered. The knowledge extraction from such a huge amount of data requires an organized scientific set of processes. This requirement has pointed out the importance of the data mining applications. As a major data mining application, classification is a supervised learning technique that requires a feature set and target class through the training process. For the training process, the key point is determining the appropriate feature set for the classification algorithm. The improvements in cutting-edge technologies such as high resolution camera systems have made extracting the insights about next pitch available. Consequently, pitch type prediction has been standing out as an important research topic. In order to predict next pitch type, existing researches mostly focus on pitcher profile, batter profile and previous pitch data in feature set. There is no study analyzing the effect of the zone information in the prediction of the next pitch type. Therefore, this study has analyzed the contribution of zone information in pitch type prediction. Our approach is that, we aimed to reveal the contribution of zones with the high strike low bat rates for pitch type decision in pitcher and batter player match up. This aim directed us to analyze the pitch type prediction problem for both zone-based and non-zone-based approaches so that we can exhibit how much zone information contributes to the problem through different classification algorithms.

اصطلاح موضوعی

Computer engineering

اصطلاح موضوعی

Internet of Things

اصطلاح موضوعی

Neural networks

مستند نام اشخاص تاييد نشده

Türkmen, Fatih

مستند نام اشخاص تاييد نشده

Ergenç Bostanoğlu, Belgin

مستند نام تنالگان تاييد نشده

Izmir Institute of Technology (Turkey)

نام الکترونيکي

فرمت انتشار

p

نوع ماده

[Thesis]

کد کاربرگه

276903

سطح دسترسي

a

تكميل شده

Y