Learning with Partially Labeled and Interdependent Data
Consider the supervised learning task, where the prediction function, which infers a predicted output for a given input, is learned over a finite set of labeled training examples, where each instance of this set is a pair constituted of a vector characterizing an observation in a given vector spac...
Đã lưu trong:
| Những tác giả chính: | , |
|---|---|
| Định dạng: | Sách |
| Ngôn ngữ: | English |
| Được phát hành: |
Springer
2015
|
| Những chủ đề: | |
| Truy cập trực tuyến: | https://scholar.dlu.edu.vn/thuvienso/handle/DLU123456789/56140 |
| Các nhãn: |
Thêm thẻ
Không có thẻ, Là người đầu tiên thẻ bản ghi này!
|
| Thư viện lưu trữ: | Thư viện Trường Đại học Đà Lạt |
|---|
| Tóm tắt: | Consider the supervised learning task, where the prediction function, which infers
a predicted output for a given input, is learned over a finite set of labeled training
examples, where each instance of this set is a pair constituted of a vector characterizing an observation in a given vector space, and an associated desired response
for that instance (also called desired output). After the training step, the function
returned by the algorithm is sought to give predictions on new examples, which have
not been used in the learning process, with the lowest probability of error... |
|---|