Classification is a supervised leaning process where the data is grouped against a known class tag. It is a task consists of discovering knowledge that can be used to forecast the class of a record whose class identify is unknown. In mammogram image classification it is used to categorize the images under different class tags depending on the characteristics of image. Classification is discrete and do not entail any order and continuous and floating point would designate a numerical target rather than categorical.
Classification is divided into two types as
i) Binary classification ii) Multi label classification.
In binary classification the data is predicted into two classes or categories. For example, in image classification it is categorized in to normal or abnormal whereas in multi label classification the data is grouped in to more than two categories such as normal, abnormal or fatty etc.
The attribute set used in classification process is partitioned into two disjoint sets as test set and training set. The test set contains the attribute set with class predefined class label. Normally, the class tag arrives from prior experiential data. The test data can be represented as: (a1, a2, …, an; c), where ai is the attribute c represents the class. Even though the class tags of these testing data are unknown, the classes that these data belong can be predicted. As shown in the figure 5.1, a classification model can be considered as a black box that automatically assigns a class tag when a attribute set of unknown classes is provided. The classification step in data mining consist of two phases as given below
1) Training Phase
2) Testing Phase
Training phase is learning step where a training model is constructed by the cla...
... middle of paper ...
...xed group of properties or attributes .
• Predefined classes : the target class tags has distinct output values (Boolean or multiclass)
• Adequate data: enough training cases should be present to train the model.
• Internal node: specifies a test on a single attribute
• Leaf node: designates the value of the target attribute
• Branch(Edge): split of one attribute
• Path: a disjunction of test to make the final decision
• Decision trees perform classification by starting at the root of the tree and moving through it until a leaf node.
• Selection of an attribute to test at each node - choosing the most useful attribute for classifying examples.
• Information gain- measures how well a given attribute separates the training examples according to their target classification. This measure is used to select the best attributes at each step when mounting the tree.
how strong and wise the tree is by all the patterns and age marks on the tree. Rings are features that can tell
Ø Amount of rainfall that runs down the tree. If it is too much, it
Based on her 2004 book Transgender Emergence: Therapeutic Guidelines for Working with Gender-variant People and Their Families, Arlene Istar Lev developed two models to describe sex, gender identity, and sexual orientation. The first is a binary model. According to Patton et al. (2016), in this binary system “sex, gender identity, gender role (the enactment of gender), and sexual orientation are assumed to align and lead to the next” (p. 176). As Lev (2004) states in her book, the binary model assumes that “if a person is a male, he is a man; if a person is a man, he is masculine; if a person is a masculine male man, he will be attracted to a feminine female woman; if a person is female, she is a woman;
1) Sort the pictures into living and nonliving categories by using their definitions that they created.
In conclusion, according to Beddow, Hymes and McAuslan (2011, p. 12), classification both provides an easy life and give a hand to stay alive however, nowadays momentarily classification is not a necessity, but it is in progress without noticing by human beings. Considering Beddow, Hymes and McAuslan (2011, p. 12) people classify things depending upon a couple of elements when the subject is human beings. According to Beddow, Hymes and McAuslan (2011, p. 12), although
The ‘New Criminology’, first published in 1973, was written to criticize all previous criminological theories, positivistic and classical however, were the main focus of critique and to eliminate crime and destroy inequality in a system which has the duality of freedom, and constraint simultaneously (Walklate, 2007). The three Neo-Marxists, Ian Taylor, with criminological theory, Paul Walton, with Marxist perspectives and Jock Young, and his strength in labelling theory approaches, incorporated all their strengths in order to create a fully reached criminological and sociological theory which would critique previous schools and expose their weaknesses(Walton, Taylor, Young, 1988). The general components of ‘New Criminology’, consists of the
The classification of different types of bonds includes ionic and covalent bonds. Although there are more types of bonds such as coordinate covalent, network covalent, and metallic we focused mostly on covalent and ionic bonds. The classification of these different types of bonds is not a complicated concept. They are classified by what they bond with and whether they are polar or non polar. For example to classify a covalent bond as a covalent bond it would have to be a non-metal element plus another non-metal element. Same goes for an ionic bond but instead it would be a metal plus a non-metal element. Another way they are classified is if they share electrons or if they make a transfer of electrons.
To classify ALL, physicians used to use what is called the French-American-British (FAB) classification to divided the disease into three categories called L1, L2, or L3, based on how the leukemia cells looked under a microscope(American Cancer Society, 2013)54. This method is now a thing...
Examine the different kinds of leaves. Classify each according to the kind of leaf blades, kinds of leaf veins, Phyllotaxy, and leaf blade morphology.
The height of a tree is the height of its root. The degree of a node is the number of children of the node. The degree of a tree is the maximum degree of the degrees of its nodes. The tree on the next page has height 3 and degree 5.
are the ones who developed the first classification scheme. During the 4th century, Aristotle grouped animals according to where they lived. On the other hand, Theophrastus grouped plants according to their stem structure. As time passes by, the ways of identification flourished. Not only did the classification system affect the branch of biology, but it also affected the entertainment industry of the modern world. Genre is an example of the categorization for modern art and entertainment. Genres, such as horror, romance, drama, comedy, and science
There are many different types of students. All students have their own way of studying and learning material. A student’s attitude is the most determining factor in how well a student performs academically. Some students are eager to learn and try their best; however, some students could care less about learning. Each year students decide whether they will succeed or fail in school. All students fall into one category or another. Students can be classified into three categories: Overachievers, Average Joes, and Do Not Give a Rips.
Sentiment analysis, also called as opinion mining, is the field of study that analyzes people’s opinions, sentiments, evaluations, appraisals, attitudes and emotion towards entities such as products, services or organizations, individuals, issues, topics and their attributes. Sentiment analysis and opinion mining mainly focuses on opinions which express or imply positive, negative or neutral sentiments. Due to the big diversity and size of social media there is a need of automated and real time opinion extraction and mining. Mining online opinion is a form of sentiment analysis that is treated as a difficult text classification task.
Machine learning systems can be categorized according to many different criteria. We will discuss three criteria: Classification on the basis of the underlying learning strategies used, Classification on the basis of the representation of knowledge or skill acquired by the learner and Classification in terms of the application domain of the performance system for which knowledge is acquired.
The history of taxonomy dates all the way back to the 4th century, where organisms were divided into 2 groups, plants and animals by a Greek philosopher, Aristotle. Early naturalists did not acknowledge that the similarities and differences between the two organisms were results of evolutionary means. So as the years went on, classification gradually changed and slowly became more and more sophisticated.