Boolean definition

Boolean data type for which you can specify the “Yes” or “No” value. For example, “DVD”.

Split View

AI-Powered Contracts

Draft, Review & Redline at the Speed of AI

Get StartedBook a Demo

Boolean. | “string | “list” | “name-value” | “structured” | empty Module usage The definitions in a module can be used in a BRAWL expression using the syntax of the action_extension, artefact_extension and resource_extension. action_extension ::= “<” action-keyword value “>” artefact_extension ::= resource_extension ::= “<” resource-keyword value “>” The keywords used in these expressions need to be defined previously in a module. A keyword must also be used in the context that it is defined for, e.g. a keyword defined in an action_extension_def can only be used in an action specification. Finally, the type of the value used must match the value defined in in the corresponding extension definition. Examples Some examples of the BRAWL language that clarify issues that may have been unclear so far. The form of these examples will be to answer the question “How do I say using BRAWL … ?”.

Boolean point of view. In a “Boolean” view of the world everything is ei- ther true or false, black or white. This does not conform to the real world in which often many “shades of grey” exist. The Boolean top-down atomic rep- resentations used in the previous chapters cannot handle these intermediate values. Secondly, the decision tree representations are based on the assumption that the data in the training set is precise, while in real world scenarios this is often not the case. In some cases the original data on which a data 58 Introduction set is based may have contained missing or empty values which have been replaced in the data preparation phase of the knowledge discovery process [85, Chapter 8]. There is also the possiblity of typing errors while inserting the data into the data base. Another potential problem is that the values in a data set may be the result of measurements which can be inaccurate. As a result there is often a degree of uncertainty as to whether the values in a data set are 100% accurate. In this chapter we will show how we can evolve fuzzy decision trees based on the top-down atomic representations from Chapter 3 by using fuzzy sets and fuzzy logic [5]. ▇▇▇▇▇ set theory and fuzzy logic are generalizations of classical (Boolean) set theory and Boolean logic. They can be used to help computer programs deal with the uncertainty of the real world. By using fuzzy sets and fuzzy logic we aim to improve two aspects of the Boolean top-down atomic representations:

Examples of Boolean in a sentence

• Registry Operator will offer Boolean search capabilities supporting, at least, the following logical operators to join a set of search criteria: AND, OR, NOT.

• Set by the DataValueType Terrasoft.Nui.ServiceModel.DataContract Possible values ( DataValueType ) Guid 0 Text 1 Integer 4 Float 5 Money 6 DateTime 7 Date 8 Time 9 Lookup 10 Enum 11 Boolean 12 Blob 13 Image 14 ImageLookup 16 Mapping 18 Value The object that contains the added column value.

• HasTaskcard Boolean Indicator if the maintenance item has any task cards.

• In order to provide an effective WHOIS database, Boolean search capabilities may be offered.

• Possible values ( DataValueType ) Guid 0 Text 1 Integer 4 Float 5 Money 6 DateTime 7 Date 8 Time 9 Lookup 10 Enum 11 Boolean 12 Blob 13 Image 14 ImageLookup 16 Mapping 18 Value object The object that contains the value of the added column.

• Set by the DataValueType Terrasoft.Nui.ServiceModel.DataContract Possible values ( DataValueType ) Text 1 Integer 4 Float 5 Money 6 Date 8 Time 9 Lookup 10 Enum 11 Boolean 12 Blob 13 Image 14 ImageLookup 16 Guid 0 Mapping 18 Value The object that contains the added column value.

• An entry level course in digital electronics to include numbering systems, logic gates, Boolean algebra, and combinational logic.

• We therefore associate conditions with countering nodes, which are Boolean functions over the attributes of the ADTree.

• Application of Boolean algebra to switching circuit design and to error detection.

• The key search terms and synonyms relating to each were combined using Boolean operators.

More Definitions of Boolean

Boolean. </boolean>" string_val ::= "<string>" string "</string>" time_val ::= "<▇▇▇>" time_of_day </▇▇▇>" location_val ::= "<location>" "Lat" integer "." integer "Lon" integer "." integer "</location>" time_ref ::= "<time_ref>" time_val "current" "spent" identifier // identifier = pid "</time_ref>"

Boolean representations of Chapter 3 can be changed into fuzzy repre- sentations. An example of a fuzzy decision tree is shown in Figure 4.2, its meaning will be explained in Section . In a fuzzy decision tree we do not have the less-than (<), greater-equal-than ( ) and set operators used by the clustering and partitioning representations for the numerical valued at- tributes, but instead we use more intuitive fuzzy terms like Young and Tall which correspond to specific fuzzy sets. These fuzzy sets are defined through a process, called fuzzification, which defines a (fixed) maximum number of fuzzy sets for the domain of each numerical valued attribute. AGE = Y oung No Yes

Boolean means that the value shall be either ‘yes’ or ‘no’.