Practical classification issues;
It can solve both regression and classification problems with large data sets.
It is not only a classification problem, but also a timing problem..
It is not only a classification problem but also a timing problem..Combinations with other parts of speech
Not every regression or classification problem needs to be solved with.
Not only is it a classification problem, but it is also a timing problem..
In a classification problem, we are trying to predict discrete-valued outputs.
It is not only a classification problem, but also a timing problem..
Not every regression or classification problem needs to be solved with deep learning.
With classification problem, is the accuracy index completely reliable?
This tutorial uses a neural network to solve the Iris classification problem.
To simplify the classification problem.
The topic of classification was given particular emphasis at the 2003 Voorburg Group meeting.
And the problem in classification is to find a decision boundary.
Issues of classifications.
We can then leverage regression for classification problems, via logistic regression:.
The issue of classification should be addressed in the Committee on Specific Commitments.
There are problems with classification and the level of details is limited;
This challenge falls under the category of a classification problem.
Support vector machines(SVM) find optimal solutions for classification problems.对于回归问题,这可能是平均输出值,对于分类问题,这可能是多数的(或最常见的)类值。
For regression problems,this might be the mean output variable, for classification problems this might be the mode(or most common) class value.两项案件都涉及分类问题,以及承诺时间表的范围和覆盖面。
Both cases involved classification issues, along with the scope and coverage of schedules of commitment.对于回归问题,这可能是平均输出变量,对于分类问题,这可能是模式(或最常见)类值。
For regression problems,this might be the mean output variable, for classification problems this might be the mode(or most common) class value.对于一些分类问题,用多语言词嵌入训练的模型展现的跨语言性能非常接近于特定语言分类器的性能。
For some classification problems, models trained with multilingual word embeddings exhibit cross-lingual performance very close to the performance of a language-specific classifier.国际经济和社会分类专家组于2009年9月1日至4日再次开会,讨论了一系列广泛的分类问题。
The Expert Group on International Economic and Social Classifications met again from 1 to 4 September 2009 anddiscussed a wide range of classification issues.最初是为了分类问题而设计的,但是我们将在这章中看到,它也可以很好地扩展到回归问题上。
It was originally designed for classification problems, but as will be seen in this chapter, it can profitably be extended to regression as well.现在,我们讨论一类与此相似的用于解决分类问题的模型。
We now discuss an analogous class of models for solving classification problems.不同于古典控制和分类问题,解决方案是复杂的,并且必须被发现和优化在多维空间。
Unlike classical control and classification problems, the solutions are complex and must be discovered and optimized in multidimensional space.鸢尾花分类问题是监督式机器学习的一个示例:模型通过包含标签的样本加以训练。
The Iris classification problem is an example of supervised machine learning: the model is trained from examples that contain labels.