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How to structure and write a UK dissertation research proposal
Overview on various types of literature review
Supervised and unsupervised learning of machine learning
Moves in the Literature review and Schematic Structure
The primary goal of writing a Literature Review
What are the types of Quantitative analysis and its research types?
How to structure and write a dissertation research proposal?
Supervised and unsupervised learning of machine learning?
Supervised Machine Learning or Supervised Machine must be trained on well-labelled or well-aligned data. The majority of the algorithms in Supervised Machine Learning would be classification and regression algorithms. Here are some examples of Supervised Machine Learning.
Regression Linear
Linear Regression is a supervised learning-based machine learning algorithm. It is used in predicting the value of a dependent variable (y) based on a given independent variable (x). As a result, this regression technique determines a linear relationship between x (input) and y. (output).
Support Vector Machine (SVM)
The “Support Vector Machine” (SVM) is a supervised machine learning algorithm that can be used to solve classification and regression problems. It is, however, mostly used in classification problems. Each data item is plotted as a point in n-dimensional space (where n is the number of structures you have), with the value of each feature being the value of a specific coordinate in the SVM algorithm. Then, we perform classification by locating the hyperplane that best distinguishes the two classes (look at the below snapshot).
Forest at Random
It is a machine learning technique used for solving regression and classification problems. It uses ensemble learning, a technique that combines many classifiers to solve complex problems.
The Nave Bayes algorithm
The Nave Bayes algorithm is a supervised learning algorithm that solves classification problems and is based on the Bayes theorem.
With a high-dimensional training dataset, it is typically utilized in the training dataset.
The Nave Bayes Classifier is a simple and effective classification technique that helps in the building of fast machine learning models that can make accurate predictions.
It’s a probabilistic classifier, which means it makes predictions based on the probability of an object.
Unsupervised Machine Learning, as the name suggests, does not require supervision. A set of untagged data will be fed to unsupervised machine learning.
Hierarchical clustering
Clustering using K-means
K-nearest neighbours
Detection of anomalies
Artificial Neural Networks
These machine learning algorithms will be useful in Data Science, Data Mining, Big Data Analytics, Artificial Intelligence, and Cloud Computing applications.
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Reference:
Alloghani, M., Al-Jumeily, D., Mustafina, J., Hussain, A., & Aljaaf, A. J. (2020). A systematic review on supervised and unsupervised machine learning algorithms for data science. Supervised and unsupervised learning for data science, 3-21.