Data mining is a major area that is present in PhD research to carry out a new study. In common the field of data mining stands to extract a particular data from large storage. Mining is the process that requires to predict a particular data and the data can be of any type. Hereby we give you the main types of data mining in PhD.  

What can be in Data Mining?

• Web Mining
• Pattern Mining
• Image Mining
• Video Mining
• Text Mining
• Opinion Mining

    Even though the data differs in complete with one another, the processing steps are same. The data from each database can be of similar data. For example, in text mining a search of similar text from the whole database requires certain process. Hence, for any type of data it requires to perform the following procedure.   

    Let us consider the issue of COVID-19, if you need to extract the number of male and female in treatment, then data mining approach can be in use. Not only this, you can also extract the patients in particular ward and so on. As per this example, the dataset should have the features as name, contact details, gender, date, time, temperature, vaccine dosage and so on. Now let us know about each process and its purpose.

1. Pre-Processing – It cleans the dataset, that means to reduce redundancy, data transformation, normalize, correlate and others. As per the data and the dataset features, the pre-processing steps has to be in use. It is not that all the steps in pre-processing will result in better output. Hereby we give few normalization methods,

• Min-Max
• Decimal scaling
• Zero-mean
• And so on

2. Feature extraction and Selection – In data mining, the features will be in large number that extracts one by one from the full dataset. Since it has many number of features, only a set of features are important. So we can identify it from optimization methods. The feature selection can be using anyone below,

• Genetic algorithm
• K-nearest neighbour
• Random forest
• Neural network
• Convolution neural network
• And so on

3. Clustering – The process of clustering forms different groups in a dataset which makes the next process easier. It performs with respect to the specific features that are similar in certain constraint. This is more efficient when the size of the dataset increases. Some of the clustering methods are,

• k-means++
• DBSCAN
• Fuzzy C-means
• OPTICS
• CURE
• And so on

4. Classification – Classifier presents to categorize the data as per the given request. Machine learning algorithms are popular for classification, in recent days artificial intelligence is also able to categorize the data. Now let us have a glance on classifiers as below,

• Naïve Bayes
• Linear and Logistic Regression
• Support Vector Machine
• Decision tree
• Bayesian Belief Networks
• ID3 algorithm
• And so on

   Above all the process this data mining is on many use-cases that includes event detection, abnormal traffic prediction and more. All sorts of PhD writing takes major part to develop data mining by means of PhD help with PhD Journal Paper writing, Survey Paper writing, Dissertation Writing, Thesis Writing and many more. Beyond this, the data mining also uses rule based methods to find the mine data. We are clear with all topics and so you can get benefit from our PhD guidance. Start your Journey with US From NOW!!!