learning n. 學(xué),學(xué)習(xí);學(xué)問,學(xué)識(shí);專門知識(shí)。 good at learning 善于學(xué)習(xí)。 a man of learning 學(xué)者。 New learning 新學(xué)問,新科學(xué)〔尤指十六世紀(jì)在英國(guó)傳播的宗教改革學(xué)說及用希伯來文及希臘文對(duì)于《圣經(jīng)》的考證研究〕。
Supervised learning of heuristic function for refutation 反演啟發(fā)函數(shù)的監(jiān)督學(xué)習(xí)算法
The former belongs to supervised learning and the latter belongs to unsupervised learning 它們分屬于有監(jiān)督學(xué)習(xí)與無監(jiān)督學(xué)習(xí)。
A semi - supervised learning system was proposed based on art ( adaptive resonance theory ) 摘要根據(jù)自適應(yīng)諧振理論提出了半監(jiān)督學(xué)習(xí)自適應(yīng)諧振理論系統(tǒng)。
Supervised learning with the use of regression and classification networks with sparse data sets will be explored 也將在課程中以帶有稀疏值理論的分類神經(jīng)網(wǎng)絡(luò)與回歸的使用來探討監(jiān)督式學(xué)習(xí)。
The distinct difference between supervised learning and unsupervised learning lies in whether the example consists of the pre - processed output value 這兩種方法最大的區(qū)別就在于學(xué)習(xí)樣本是否包含有預(yù)先規(guī)定好的輸出值。
It also proposes a method of supervised learning to train the decision function and provides the corresponding method of calculation to realize it 提出了一種通過監(jiān)督學(xué)習(xí)來訓(xùn)練判別函數(shù)的方法,并給出了相應(yīng)的實(shí)現(xiàn)算法。
Classification is a sort of supervised learning ( i . e . , the learning of the model is " supervised " in that it is told to which class each training sample belongs ) 需要指出的是:分類是一種有指導(dǎo)的學(xué)習(xí)(即模型的學(xué)習(xí)在被告知每個(gè)訓(xùn)練樣本屬于哪個(gè)類的“指導(dǎo)”下進(jìn)行) 。
Supervised learning is the machine learning task of inferring a function from labeled training data. The training data consist of a set of training examples.