Classification Methods Uses set of parameters to characterize each object Features should be relevant to task at hand Supervised classification What classes??? Set of sample objects with known classes Training set Set of known objects Used by classification program Two phases for classification ?? ??
Classification Methods1. Training Phase: Uses training set Decision is about How to weight parameters How to combine these objects under different classes1. Application Phase: Weights determined in phase 1 are used with set of objects That do not have known classes Determine their possible class
Classification Methods With few parameters ; process is easy Example: With much more parameters ; process is tough Example: Depending on structure ; find types of attributes Multi State Attribute Example: Binary State Attribute Example: Numerical Attributes Example
Classification Methods Binary State Bold , underline Multi State Color , position , font type Execution of operation changes attribute value. Example: MOVE FILL INSERT DELETE CREATE
Classification Methods Relation between Classes & Properties 1. Monothetic: To get membership of class , object must posses the set of properties which are necessary as well as sufficient Example 1. Polythetic: Large number of members have some number of properties No individual is having all the properties example
Classification Methods Relation between Object & Classes 1. Exclusive: Object belongs to single class Example 1. Overlapping: Membership is with different classes Example
Classification Methods Relationship between Classes & Classes: 1. Ordered: Structure is imposed Hierarchical structure Example 1. Unordered: No imposed structure All are at same level example
Measures of Association Some classification methods are based on a binary relationship between objects On the basis of this relationship a classification method can construct a system of clusters Relationship type: 1. similarity 2. dissimilarity 3. association
Measures of Association Similarity: The measure of similarity is designed to quantify the likeness between objects so that if one assumes it is possible to group objects in such a way that an object in a group is more like the other members of the group than it is like any object outside the group, then a cluster method enables such a group structure to be discovered.
Measures of Association Association: Association means??? Dependency… Occurrence… reserved for the similarity between objects characterized by discrete-state attributes.
Measures of Association Used to measure strength of relationship measure of association increases as the number or proportion of shared attribute states increases. Five measures of association 1. Simple 2. Dice’s coefficient 3. Saccard’s coefficient 4. Cosine coefficient 5. Overlap coefficient
Measures of Association Used in information and data retrieval | | specifies size of set
Probabilistic Indexing Probability of relevance Experiments and observations Sample space May Consist relevant as well as non relevant objects Consider a document Find no. of relevant document with respect to it That gives probability quotient probability measured as per the terms present in document
Probabilistic Indexing Probabilistic indexing model Contains random variable Denotes no. of relevant documents If this variable is selected by system Gives possible relevant document description Probabilistic information retrieval models are based on the probabilistic ranking principle, which says that documents should be ranked according to their probability of relevance with respect to the actual request.