MZ@ !L!This program cannot be run in DOS mode. $ ۭcccRgcjecRichcPELٿ=! *( 4 Pp.textT@@.rsrc @@.reloc @Bm=Ol=HHHHMSDMine.RLL @"Xp0H`!x"1ABCQR a8qPh1ABCQa(@Xp           0 @ P ` p             0 @ P ` p     hPH0+b-r`20:&X?L.EzT< ] hQ:dpXgb@lHmx~<`PKj0PzPchZ k8v(pjz&4VS_VERSION_INFO?StringFileInfo040904b0LCompanyNameMicrosoft CorporationFFileDescriptionMicrosoft OLE DB Provider for Data Mining Services - Resource Strings2 FileVersion8.00.760 InternalName1LegalCopyright 1988-2003 Microsoft Corp. All rights reserved.sLegalTrademarksMicrosoft is a registered trademark of Microsoft Corporation. Windows(TM) is a trademark of Microsoft Corporation@ OriginalFilenamemsdmine.rlln'ProductNameMicrosoft SQL Server Analysis Services6 ProductVersion8.00.760DVarFileInfo$Translation The element was not found End Of DataKThe prediction succeeded, but unknown values or attributes were encounteredMThe following aggregated DM providers were successfully loaded in-process: %1eWarning: The following aggregated DM providers currently loaded in-process are potentially unsafe: %1!Unable to load the parsing tablesUnknown parsing errorCatastrophic parse failure$The mining model '%1' already exists'The data mining database already existsNo query was providedUnknown algorithmUnknown command3Query column [%1] cannot be converted to model type4Analysis Services component error (has to be mapped)Unexpected end of statement?Reference column '%1' does not exist within the current contextThe model '%1' does not exist invalid value in DMColumn member"Case consumer initialization error9A discrete operation was attempted on a continuous column4Initial catalog was not specified, or it was invalidYA column with the specified name already exists in the current context (%1 = column name)@An operation that can be performed only during training occurred Integer conversion error on '%1'Real conversion error on '%1'+The syntax requires a table column for '%1',The syntax requires a scalar column for '%1'GTable column '%1' does not allow a distribution to be specified with itMTable column '%1' does not allow a modeling qualifier to be specified with itiTable column '%1' does not allow a content type (discrete, continuous, and so on) to be specified with itkTable column '%1' does not allow a content qualifier (ordered, cyclical, and so on) to be specified with iteTable column '%1' does not allow a column qualifier (key, support, and so on) to be specified with itQSubselect from clause has an unexpected type (other than a colref or a histogram)The file '%1' is already openedThe file '%1' does not existSharing violation on file '%1'General file error: %13The context of the $<column> reference is incorrect1The column '%1' was expected to be a nested table1Error initializing IDataConvert interface pointer,Error initializing IMalloc interface pointer,Nested SHAPE constructions are not supportedEAssociative specifications are allowed to chapter (table) column only6The root location was not specified, or it was invalid;The file '%1' was not opened (requested for this operation)Dimension '%1' does not existHierarchy '%1' does not existLevel '%1' does not existProperty '%1' does not existMeasure '%1' does not exist Dimension '%1' is already in use Hierarchy '%1' is already in useLevel '%1' is already in useProperty '%1' is already in useMeasure '%1' is already in use#Unknown type on load of column '%1'+Unknown distribution on load of column '%1')Unknown relation '%1' discovered on load Invalid schema restrictions: %17Error initializing IErrorClassFactory interface pointerrInvalid selection list for a SELECT ... FROM <dmm>.CONTENT statement (only schema column references are supported)?Invalid WHERE clause in SELECT ... FROM <dmm>.CONTENT statementUnable to parse XML stringInvalid mining model flag '%1'MThe mining model flag '%1' is not valid for the current data mining algorithm6The mining model flag '%1' is specified more than once9The mining model flag '%1' has an invalid data type value0Training seed must be between 1 and %1 inclusivenInvalid selection list for a SELECT ... FROM <dmm>.XML statement (only schema column references are supported)4Invalid value for Mining EXecution Location propertygCannot execute remotely - no server connection available. Check the Mining Execution Location property.HTree operator is invalid without restriction for NODE_UNIQUE_NAME columnLMining model remains in an untrained state due to insufficient training dataOnly SELECT statements can be executed remotely on the Analysis Server (use DSO for model creation/maintenance). Check Mining Execution Location property.|Could not find a local mining model named '%1' to execute this statement on (it cannot be executed on server mining models).JAnalysis Server does not allow use of the provider specified in OPENROWSET%Invalid XML in model '%1' around '%2'The mining model is already trained and does not support incremental update. You must use DELETE * FROM <dmm> before you use INSERTA resource was not found:The value of the 'Extended Properties' property is invalidThe model is not trained&Selections from model must be distinct,The insertion and query columns do not match'%1' is not the current catalog?Error setting LCID or CompareString flags during initialization5Sample percentage must be between 1 and 100 inclusive5Holdout percentage must be between 1 and 99 inclusive-External provider '%1' failed with error '%2'+Unknown token specified outside of training!Invalid state '%2' on column [%1]=Column [%1] is not a valid RELATE TO target in a nested tableGThe column [%1] is in a RELATE TO relation and is of a nondiscrete type1Invalid relation in the definition of column [%1]9Different properties were specified in the same hierarchy3Circular reference in the definition of column [%1]$Discretization failed on column [%1]HTable column [%1] is inside another table column, which is not supportedAn empty prediction is obtainedETable-returning expressions cannot be used in calculation expressionsInvalid FROM clause;The WHERE clause must contain a logical/relational operatorSTwo SELECT expressions in a UNION statement must produce the same number of columns:An attempt to predict a nonpredictable column was detectedA table.column column reference cannot be used in a SELECT list, a FROM clause, or the WHERE clause of a SELECT statement with PREDICTION JOINOnly predictable columns, columns that are related to a predictable column, or columns inside a predictable table column can select from the mining model\The first argument for Top*/Bottom* functions is invalid. The expression must return a tableXThe second argument for Top*/Bottom* functions is invalid. It must be a column referencefThe third argument for Top*/Bottom* functions is invalid. It must be a nonnegative constant expression7No function can be used in <SELECT DISTINCT FROM model>8Invalid column reference in <SELECT DISTINCT FROM model>APrediction function '%1' cannot be used in the given FROM context0Invalid argument for a prediction function, '%1'.No cluster function can be used in the context"Invalid flag is given in Predict()<A Boolean operand is expected in an AND, OR, or NOT operatorInvalid SELECT statementInvalid column referenceFunction '%1' is not supportedmStatistics on table prediction can be used only when there is at most one predictable column inside the tableVA Boolean expression cannot either be selected or used inside an arithmetic expression<Range function '%1' cannot be used in the given FROM context+Invalid argument for a range function, '%1'>Function '%s' cannot be used in SELECT DISTINCT ... FROM modelInvalid operator usedRAggregate functions cannot be used together with nonaggregate functions or columns=Aggregate functions can only be used in top-level SELECT list>WHERE clause is not supported if an aggregate function is used2Connection failed with error '%2' on provider '%1'3Query failed with error '%2' on input provider '%1'Errors occurred during training)Column [%1] cannot be distinctly selected8Unrelated columns cannot be distinctly selected togetherLThere are too many distinct states in column [%1] for the selected algorithmInvalid ON mapping*Read NULL value on nonnullable column [%1] Duplicate columns on INSERT INTO8Not all key columns were specified for nested table [%1]/Related clauses of appended tables do not match:Incorrect row ordering or duplicate keys detected on SHAPE&Data read error on case %1 column [%2]&Data read error on case %1 column [%2],Data conversion error on case %1 column [%2]&Data read error on case %1 column [%2]*Data overflow error on case %1 column [%2]0Integrity violation error on case %1 column [%2]%Permission denied case %1 column [%2]-Schema violation error on case %1 column [%2]*Sign mismatch error on case %1 column [%2]&Data read error on case %1 column [%2]UInput provider does not support restart functionality required to train mining modelsInput provider read error '%1'YThe column [%1] is declared to be both predictable and continuous, which is not supportedQThe column [%1] is declared to be both key and continuous, which is not supporteduThe column [%1] is declared to be both discrete and having normal (or lognormal) distribution, which is not supportedgBecause the column [%1] is declared to be related to another column, a distribution cannot be specifiedThere are no predictable columns declared but the model uses the Microsoft Decision Trees algorithm, which requires the existence of at least one predictable column(The model flag '%1' has an invalid valueiThe column [%1] is declared of having type text but is not discrete or key (this is a required condition):The aggregation type for the measure [%1] is not supported/There are no key columns declared for the model;There are no key columns declared for the nested table [%1]XThe column [%1] is declared to be in an OF relation with the key, which is not supportedGThe column [%1] is in a RELATE TO relation and is of a nondiscrete typehThe column [%1] is declared to be in an OF relation but it has an invalid content type for this relationJThe columns [%1] and [%2] are logically duplicates, which is not supportedThe column [%1] is declared to be the reference of an OF relation for the column [%2], but it has an invalid content type for this relation|Because the virtual dimension '%1' was created using SQL Server 7.0 OLAP Services, it cannot be used in an OLAP mining model[The column [%1] is declared as being key and having a modeling flag, which is not supportedoThe column [%1] is declared to be both a predictable and a RELATED TO entity (property), which is not supportedaThe model [%1] is a server mining model, being available for INSERT INTO statements only from DSO\The model [%1] is a server mining model, being available for DELETE statements only from DSOZThe model [%1] is a server mining model, being available for DROP statements only from DSO\The model [%1] is a server mining model, being available for RENAME statements only from DSO~The hierarchy '%1' must use at least one level that is not an (All) level; otherwise it cannot be used in an OLAP mining modelDThe PREDICTION JOIN entity '%1' was expected to be a singleton queryJThe value '%1' is an invalid bucket count for the DISCRETIZED content type.Syntax error at line %1, offset %2, token '%3'The expression list of a select statement must contain aggregation functions, but the expression selected in position number %1 (under the name: %2) is not aggregatedThe expression list of a select statement must not contain aggregation functions, but the expression selected in position number %1 (under the name: %2) is aggregated9An unknown error was encountered in the prediction engine3This operation cannot be performed during training.$This model has already been trained.$This model has not yet been trained.#No input attributes were specified.JThe decision tree algorithm cannot build a tree for a continuous attributeInvalid cluster ID.#Failure during loading of model XML=The discrete attribute value is out of range (0..0x007FFFFFL)@The continuous attribute value is out of range (-3.4E38..3.4E38)LMining model remains in an untrained state due to insufficient training dataGAn unknown error was encountered in the Data Mining Provider AggregatorpErrors occurred while initializing aggregatable DM providers - the following provider(s) will not aggregated: %18The specified DM provider (ProgID='%s') is not availableRSchema rowset from a provider does not comply with the OLE DB for DM specificationZErrors occurred while getting model lists from the following aggregatable DM providers: %1aErrors occurred while getting supported services from the following aggregatable DM providers: %1ZAggregatable DM provider '%1'does not support mandatory security interface for aggregationErrors occurred while initializing security interfaces on the following aggregatable DM providers (they will not be aggregated): %1KInvalid XML in '%2' node getting properties for aggregated DM provider '%1'3Microsoft OLE DB Provider for Data Mining ServicesMicrosoft Decision Trees&The Microsoft Decision Trees algorithm chooses significant characteristics in the data and narrows sets of data based on those characteristics until clear correlations are established. Decision trees are useful when you want to make specific predictions based on information in the source data.Microsoft ClusteringClustering finds natural groupings of data in a multidimensional space. Clustering is useful when you want to see general groupings in your data.$Identifies the algorithm used to control the growth of a decision tree. This algorithm selects the attributes that constitute the tree, the order in which the attributes are used, the way in which the attribute s values should be split up, and the point at which the tree should stop growing.KDescribes the various ways that SCORE_METHOD should consider splitting up an attribute s values. For example, if an attribute has 5 potential values, the values could be split into a binary partition (for example, 3 and 1,2,4,5), or the values could be split into 5 separate partitions, or some other combination may be considered.Controls the growth of the tree by preventing the creation of leaf nodes that contain fewer than MINIMUM_LEAF_CASES cases. For example, if SCORE_METHOD is considering a split on a node that contains 30 cases, and the value of MINIMUM_LEAF_CASES is 10, and one potential branch of the split receives 23 of the cases while the other branch receives 7 cases, then the split will not be allowed.A floating point number between 0 and 1 that acts as a penalty for growing a tree. The parameter is applied at each additional split. A value of 0 applies no penalty, and a value close but not equal to 1 (1.0 is outside the range) applies a high penalty. Applying a penalty will limit the depth and complexity of learned trees, which avoids overfitting. However, using too strong a penalty may adversely affect the predictive ability of the learned model.Identifies the algorithm used to group cases into clusters. Some algorithms are faster or better scaled to large data sets, but there may be some cost, such as quality.Controls the number of times the algorithm will try to cluster before selecting the best answer from the set of tries. Because clustering algorithms involve some randomness, different attempts at clustering may produce quite different results.HHow many clusters of similar cases the algorithm should attempt to find. Clustering algorithms repeatedly scan the data. With each iteration they get closer to an optimal solution. This parameter controls how little a solution should change between iterations in order to be considered complete (converged). The values are between 0 and 1.The minimum number of cases that can make up a cluster. If a cluster contains too few cases, it will be discarded, and it may be reassigned to a new location.KThe percentage of cases from the training query to consider while training.YThe percentage of training cases to hold out from training and use for scoring the model.2The seed for the sampling random number generator.1The seed for the holdout random number generator.Processing queryTraining column [%s]'Training marginal model: %ld cases seen5Training Clusters: candidate model %ld, iteration %ld$Training Clusters: %ld cases scannedCulling feature set9Training Trees (counting correlations): %ld cases counted*Training Trees: %ld cases left to classifyTraining mining modelScoring model: [%ld] cases seenFalse is missing existsexisting Cluster ModelAll and and or ( ) <= > = not = TrueNB10m=P:\plato\Aurum\NewSrc\DM\MSDMineR\objm_retail\i386\msdmine.pdbp0^ *H O0K10 *H 0g +7Y0W03 +70% <<<Obsolete>>>0 0 *H Ն{S9{2@6j00%J8Y]s_]ܣ0  *H 010U VeriSign Trust Network10U VeriSign, Inc.1,0*U #VeriSign Time Stamping Service Root1402U +NO LIABILITY ACCEPTED, (c)97 VeriSign, Inc.0 970512000000Z 040107235959Z010U VeriSign Trust Network10U VeriSign, Inc.1,0*U #VeriSign Time Stamping Service Root1402U +NO LIABILITY ACCEPTED, (c)97 VeriSign, Inc.00  *H 0. h|,-.  WSu3* [4 Z%}XsjxqX)X^-bXq"X/6MJ;"V~!lJGj6 -Ӵ90  *H aU>{ǒ~"Գ+[D x~rȲ㉔LNaﳤF=P4 pV*cyis.(]  γ(y)gBHaSs?OUcc00kzm\obOC0  *H 010U VeriSign Trust Network10U VeriSign, Inc.1,0*U #VeriSign Time Stamping Service Root1402U +NO LIABILITY ACCEPTED, (c)97 VeriSign, Inc.0 010228000000Z 040106235959Z010U VeriSign, Inc.10U VeriSign Trust Network1;09U 2Terms of use at https://www.verisign.com/rpa (c)011'0%UVeriSign Time Stamping Service0"0  *H 0 za벧c+aހ='9)fHOO^/Ǒ{!NXc-)pP햻@۾%BU狙1L$*MhaXr0HO/oc ىʂ{K(Łh@F:?6LTBZze{GT=3*^:.uk=`BO[?"1s+FLmP.K*xt=,G100@+40200+0$http://ocsp.verisign.com/ocsp/status0 U00DU =0;09 `HE0*0(+https://www.verisign.com/rpa0U% 0 +0 U0  *H -Oc`,$R 볼g#F M|z 02h2;'{>! Ř@W%误j;#)]@US6:9ess2үc@0  *H 0p1+0)U "Copyright (c) 1997 Microsoft Corp.10U Microsoft Corporation1!0UMicrosoft Root Authority0 970110070000Z 201231070000Z0p1+0)U "Copyright (c) 1997 Microsoft Corp.10U Microsoft Corporation1!0UMicrosoft Root Authority0"0  *H 0 p;N(x^0ꢩ%_L >|Q`2kBdyvT뜆fkzb#<Ŀ-fh&:, X&F >8,(9IBlUa|`-wL陴d;P1$+=c`Xe7RӿUE:TNzmtN̖ (!W`i7Kc@0  *H  5$w\`2 >:!W,Gb;;Z6Ti$m?̪|1=pjOiCZ Ob{+7%-e%cT!RnC2gl QRǽ0 1 )M[WeIRT(~ū7,zwvj?6A5jj5EZ38nM b T?FUp:uҠ00j Oު@0  *H 0p1+0)U "Copyright (c) 1997 Microsoft Corp.10U Microsoft Corporation1!0UMicrosoft Root Authority0 001210080000Z 051112080000Z01 0 UUS10U Washington10URedmond10U Microsoft Corporation1+0)U "Copyright (c) 2000 Microsoft Corp.1#0!UMicrosoft Code Signing PCA0 0  *H  0S 04:/{m7#MҌ4$T~tG2XQ)8~:G9NnT1 :mPJ&?ˏIm>U7/`̀aBITJKٓ0ZGudӻݶ Os;:MON3 :doD4J#N`)*򄚙 p{4Af\3T?=tC9泬Hzk*ba9vn>KFGO%(0$0U% 0 +0U0[pir#Q~Mˡr0p1+0)U "Copyright (c) 1997 Microsoft Corp.10U Microsoft Corporation1!0UMicrosoft Root Authority<<>c@0 +70U)\3Y}. 4(0 +7  SubCA0 UF0U00  *H EXAHwwW_Ej9Y'-M88d"B߹/*Ϸ*|Q="mD_ddĩ,ې7Javv%$VT:>Ky_I^2i:TuMd0 U_ʖ0X'2ЅT+ 9 ~!X/^\Bo,I2q&ꛕ ֡L0H *H  19050010U VeriSign Trust Network10U VeriSign, Inc.1,0*U #VeriSign Time Stamping Service Root1402U +NO LIABILITY ACCEPTED, (c)97 VeriSign, Inc.zm\obOC0 *H Y0 *H  1  *H 0 *H  1 021218020856Z0 *H  1  !0  *H MaO5U8m|b IܦݝBNVkQP ߤܭu1,1¶5kBfQdoy,贬"8`j9-ֳl*ļv.!"e2#5g֩lRHnHd9!8qߠ'fqd얒[8x<@B+z@猗̚ x;~RY27鐡0Rh%x