RODM_create_ai_model(RODM)
RODM_create_ai_model()所属R语言包：RODM
Create an Attribute Importance (AI) model
创建一个属性的重要性（AI）模型
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This function creates an Oracle Data Mining Attribute Importance (AI) model.
这个函数创建一个Oracle数据挖掘属性的重要性（AI）模型。
用法----------Usage----------
RODM_create_ai_model(database,
data_table_name,
case_id_column_name = NULL,
target_column_name,
model_name = "AI_MODEL",
auto_data_prep = TRUE,
retrieve_outputs_to_R = TRUE,
leave_model_in_dbms = TRUE,
sql.log.file = NULL)
参数----------Arguments----------
参数：database
Database ODBC channel identifier returned from a call to RODM_open_dbms_connection
数据库的ODBC通道标识符返回调用RODM_open_dbms_connection
参数：data_table_name
Database table/view containing the training dataset.
数据库表/视图包含训练数据集。
参数：case_id_column_name
Row unique case identifier in data_table_name.
行独特的标识符的data_table_name。
参数：target_column_name
Target column name in data_table_name.
目标列名data_table_name。
参数：model_name
ODM Model name.
ODM产品型号名称。
参数：auto_data_prep
Setting that specifies whether or not ODM should perform automatic data preparation.
设置指定是否ODM应该执行自动数据准备。
参数：retrieve_outputs_to_R
Flag controlling if the output results are moved to the R environment.
船籍控制，如果输出的结果被移动到R环境。
参数：leave_model_in_dbms
Flag controlling if the model is dropped or left in RDBMS.
如果该模型被丢弃或留在RDBMS标志控制。
参数：sql.log.file
File where to append the log of all the SQL calls made by this function.
文件中追加的log所有的SQL调用此功能。
Details
详细信息----------Details----------
Attribute Importance (AI) uses a Minimum Description Length (MDL) based algorithm that ranks the relative importance of attributes in their ability to contribute to the prediction of a specified target attribute. This algorithm can provide insight into the attributes relevance to a specified target attribute and can help reduce the number of attributes for model building to increase performance and model accuracy.
属性的重要性（AI）采用了最小描述长度（MDL）的算法，居属性的相对重要性在指定的目标属性的预测作出贡献的能力。该算法能够洞察到指定的目标属性相关的属性，可以帮助减少属性的数量模型建设，以提高性能和模型的准确性。
For more details on the algotithm implementation, parameters settings and characteristics of the ODM function itself consult the following Oracle documents: ODM Concepts, ODM Application Developer's Guide, and Oracle PL/SQL Packages: Data Mining, listed in the references below.
欲了解更多详细信息，上的algotithm的实施，参数设置和ODM功能本身的特点，参考以下Oracle文件：ODM的概念，ODM应用程序开发指南，Oracle的PL / SQL程序包：数据挖掘，下面的参考文献中列出。
值----------Value----------
If retrieve_outputs_to_R is TRUE, returns a list with the following elements: <table summary="R valueblock"> <tr valign="top"><td>model.model_settings</td> <td> Table of settings used to build the model.</td></tr> <tr valign="top"><td>model.model_attributes</td> <td> Table of attributes used to build the model.</td></tr> <tr valign="top"><td>ai.importance</td> <td> Table of features along with their importance.</td></tr> </table>
如果retrieve_outputs_to_R是TRUE，返回一个列表，包含下列元素：<table summary="R valueblock"> <tr valign="top"> <TD> model.model_settings</ TD> <TD>表，用来设置建立模型。</ TD> </ TR> <tr valign="top"> <TD> model.model_attributes</ TD> <TD>表用于建立模型的属性。</ TD> </ TR> <tr valign="top"> <TD> ai.importance </ TD> <TD>表的功能，以及其重要性。</ TD> </ TR> </ TABLE>
（作者）----------Author(s)----------
Pablo Tamayo <a href="mailto:pablo.tamayo@oracle.com">pablo.tamayo@oracle.com</a>
Ari Mozes <a href="mailto:ari.mozes@oracle.com">ari.mozes@oracle.com</a>
参考文献----------References----------
Oracle Data Mining Concepts 11g Release 1 (11.1) http://download.oracle.com/docs/cd/B28359_01/datamine.111/b28129/toc.htm
Oracle Data Mining Application Developer's Guide 11g Release 1 (11.1) http://download.oracle.com/docs/cd/B28359_01/datamine.111/b28131/toc.htm
Oracle Data Mining Administrator's Guide 11g Release 1 (11.1) http://download.oracle.com/docs/cd/B28359_01/datamine.111/b28130/toc.htm
Oracle Database PL/SQL Packages and Types Reference 11g Release 1 (11.1) http://download.oracle.com/docs/cd/B28359_01/appdev.111/b28419/d_datmin.htm#ARPLS192
参见----------See Also----------
RODM_drop_model
RODM_drop_model
实例----------Examples----------
# Determine attribute importance for survival in the sinking of the Titanic [确定属性的重要性在泰坦尼克号沉没的生存]
# based on pasenger's sex, age, class, etc.[根据pasenger的性别，年龄，阶级，等等。]
## Not run: [＃不运行：]
DB <- RODM_open_dbms_connection(dsn="orcl11g", uid="rodm", pwd="rodm")
data(titanic3, package="PASWR")
db_titanic <- titanic3[,c("pclass", "survived", "sex", "age", "fare", "embarked")]
db_titanic[,"survived"] <- ifelse(db_titanic[,"survived"] == 1, "Yes", "No")
RODM_create_dbms_table(DB, "db_titanic") # Push the table to the database[按下表的数据库]
# Create the Oracle Data Mining Attribute Importance model[创建Oracle数据挖掘属性的重要性模型]
ai <- RODM_create_ai_model(
database = DB, # Database ODBC connection[数据库的ODBC连接]
data_table_name = "db_titanic", # Database table containing the input dataset[数据库表中输入数据集]
target_column_name = "survived", # Target column name in data_table_name[目标列名data_table_name]
model_name = "TITANIC_AI_MODEL") # Oracle Data Mining model name to create[Oracle数据挖掘模型的名称来创建]
attribute.importance <- ai$ai.importance
ai.vals <- as.vector(attribute.importance[,3])
names(ai.vals) <- as.vector(attribute.importance[,1])
#windows(height=8, width=12)[窗口（高度= 8，宽度= 12）]
barplot(ai.vals, main="Relative survival importance of Titanic dataset attributes",
ylab = "Relative Importance", xlab = "Attribute", cex.names=0.7)
ai # look at the model details[在模型的详细信息]
RODM_drop_model(DB, "TITANIC_AI_MODEL") # Drop the model[掉落的模型]
RODM_drop_dbms_table(DB, "db_titanic") # Drop the database table[删除数据库中的表]
RODM_close_dbms_connection(DB)
## End(Not run)[＃（不执行）]
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注：
注1：为了方便大家学习，本文档为生物统计家园网机器人LoveR翻译而成，仅供个人R语言学习参考使用，生物统计家园保留版权。
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发表于 2012-9-27 22:50:42
