We learned that in order to create a good classification tree model, we need to have an existing data set with known output from which we can build our model.
我们了解了为了创建一个好的分类树模型，我们必须要有一个输出已知的现有数据集，从这个数据集才能构建我们的模型。
This model can be used for any unknown data instance, and you are able to predict whether this unknown data instance will learn classification trees by asking them only two simple questions.
这个模型可用于任何未知的数据实例，来预测这个未知数据实例是否通过只询问两个简单问题就能理解分类树。
The new data has no classification (in this case, no checks on heart disease have been made) and the scoring process assigns a prediction to each new record according to the mining model.
新的数据没有分类别（这里是指还没有做过心脏病检查），评价过程根据挖掘模型将一个预测赋给每个新的记录。
I wanted to take you through the steps to producing a classification tree model with data that seems to be ideal for a classification model.
我本想带您亲历用适合于分类模型的数据生成一个分类树的全过程。
Financial Services Data model (FSDM) provides a classification model for concepts and information domains in banking.
金融服务数据模型(Financial Services Data Model,FSDM)提供银行业务的概念和信息领域的分类模型。
The effect of time delay unit number on classification precision and the performance of TDNN classifier using three typical aircraft dark room data measured with scale model were studied.
还利用三种飞机缩比模型的暗室测量数据，研究了时延神经网络分类器中时延单元数目对分类精度的影响以及分类器的分类性能。
This thesis applies data mining techniques to customer segmentation based on customer value matrix and builds the classification model of customer with different value.
本文把数据挖掘技术应用于基于客户价值矩阵的客户价值细分中，建立各类价值客户的分类模型。
A new predication method of customer credit of Banks is proposed based on the support vector domain classification model of non-balance data set.
基于非平衡数据集的支持向量域分类模型，提出了一种银行客户个人信用预测方法。
The gene linear profile model, composed of model profiles and coefficients, is obtained by ica from gene expression data, so gene classification based on ica is presented.
利用ICA对基因微阵列表达谱数据进行分解获得由基因模型谱和对应系数构成的线性谱模型，并在此基础上进行基因分类。
Data classification and prediction is the two forms of data analysis, can be used to extract important data to describe or predict the future trend of the data model.
数据分类和预测是两种数据分析形式，可以用于提取描述重要数据类或预测未来的数据趋势模型。
A support vector regression method based on classification is presented to solve the nonlinear regression problem with unknown data distribution and mathematical model.
提出了一种基于分类技术的支持向量回归方法，解决数据分布未知、数学模型未知的非线性回归问题。
The thesis also examines the rough set model based on classification accuracy. The MIE-RS data mining approach given later is based on the model.
另外，作者提出了基于分类正确度的粗糙集模型，该模型已用于作者研制的数据挖掘方法MIE-RS上。
In comparison with the maximum likelihood classification by field survey data, the classification precision of this model heightens 16%.
结合实地调查数据与最大似然分类算法进行对比实验，表明该模型比最大似然总体分类精度高16%。
Decision tree is an important method in induction learning as well as in data mining, which can be used to form classification and predictive model.
决策树是归纳学习和数据挖掘的重要方法，通常用来形成分类器和预测模型。
Future studies from the selected variables and quantify sample volume increased data model function form the real estate market, such as classification of different nature, for further study.
未来的研究可以从变量的选取和量化、增大数据样本量、模型函数形式、房地产市场不同性质分类等方面，进行进一步研究。
Even for binary, linear classification it is data dependent whether it is better to train the geometrical model (SVM?) or a probabilistic one.
即使是二进制的，线性分类它是依赖于数据是否是更好的列车的几何模型(SVM ？)或概率。
Using the concept of classification of clustering, the behavior data were classified by probability and frequency, and the model was built for intelligence information analysis.
利用概念分类的聚类思想，使用概率和频率度量对行为数据分类，获得指导情报分析的模型。
In the data mining stage, the paper first the data in the data mining model attribute classification.
在数据挖掘阶段，论文首先对数据挖掘模型中的数据进行属性分类。
We applied the model to analyze the expression data set of leukaemia. The experimental result proved that this model can get cluster Numbers automatically and a high accuracy of classification.
将该种模型运用于公开的白血病基因表达数据集进行实验，实验表明该方法能自动获取基因表达数据的聚类数，并得到较高的分类准确率。
Methods The data on 343 kinds of infectious disease symptoms, signs were collected and Bayesian classification model was constructed.
方法收集343种传染病症状、体征数据，运用贝叶斯算法建立分类模型。
Classification is a very important task of data mining, its purpose is to find out classifying function or classifying model.
分类是数据挖掘中一项十分重要的任务，其目的是找出分类函数或者分类模型。
Kernel Methods are concerned with mapping input data into a higher dimensional vector space where some classification or regression problems are easier to model.
核函数方法关心的是如何把输入数据映射到一个高维度的矢量空间，在这个空间中，某些分类或者回归问题可以较容易地解决。
Kernel Methods are concerned with mapping input data into a higher dimensional vector space where some classification or regression problems are easier to model.
核函数方法关心的是怎样把输入数据映射到一个高维度的矢量空间，在这个空间中，某些分类或者回归问题可以较容易地解决。
The authors get the result that way 2 is better than way 1 by processing data, making use of least squares method, volume model and classification exchange model.
我们利用最小二乘法、体积模型、等级换算模型对数据进行处理，得出方法二比方法一的准确性略高。
The method can reduce the dimensions of the data set and the complexity of the model of SVMs, and doesn't affect its classification and prediction performance.
该方法可降低数据空间维数和支持向量机处理过程的复杂度，但不会降低分类和预测性能。
Classification, which is able to analyze and learn mass of relative data, establish corresponding classification model in some fields, is an important technique for data mining.
在数据挖掘中，分类是一种重要的技术，它能对大量有关数据进行分析、学习，并建立相应问题领域中的分类模型。
Classification is an important sub-branch of data Mining, which can find out a model describing a predetermined set of data classes or concepts as used to predict the class label for a test sample.
分类是数据挖掘的一个重要分支，分类能找出描述数据类或概念的模型(或函数)，以便能使用模型预测类标记未知的对象类。
The destination of classification is to learn a classification function or classification model that can map a data item to a preassigned class.
分类的目的是学会一个分类函数或分类模型，该模型能把数据库中的数据项映射到给定类别中的某一个。
The destination of classification is to learn a classification function or classification model that can map a data item to a preassigned class.
分类的目的是学会一个分类函数或分类模型，该模型能把数据库中的数据项映射到给定类别中的某一个。
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