Podcast
Questions and Answers
Which type of learning method is clustering?
Which type of learning method is clustering?
- Unsupervised learning (correct)
- Semi-supervised learning
- Supervised learning
- Reinforcement learning
Clustering is used for which type of analysis?
Clustering is used for which type of analysis?
- Predictive analysis
- Causal analysis
- Descriptive analysis
- Exploratory analysis (correct)
Which of the following is an example of clustering application?
Which of the following is an example of clustering application?
- Classifying images
- Segmenting customers for marketing (correct)
- Predicting stock market trends
- Detecting fraud in financial transactions
How is similarity between two observations measured in clustering?
How is similarity between two observations measured in clustering?
What is the main characteristic of observations within each group in clustering?
What is the main characteristic of observations within each group in clustering?
True or false: Clustering is a supervised learning method.
True or false: Clustering is a supervised learning method.
True or false: Clustering is used for exploratory analysis.
True or false: Clustering is used for exploratory analysis.
True or false: Clustering groups data into sets of related clusters.
True or false: Clustering groups data into sets of related clusters.
True or false: Observations within each group in clustering are less similar to each other than observations within other groups.
True or false: Observations within each group in clustering are less similar to each other than observations within other groups.
True or false: Similarity between two observations in clustering is measured as similarity between their target attributes.
True or false: Similarity between two observations in clustering is measured as similarity between their target attributes.
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Study Notes
Clustering Concept
- Clustering is an unsupervised learning method for grouping data without prior knowledge of the groups.
- It doesn't require labelled data or a target attribute for prediction or classification.
Characteristics of Clustering
- All attributes are considered in the analysis.
- The groups are not known in advance.
- Clustering is used for exploratory analysis.
Applications of Clustering
- Segmenting customers who share similar interests for marketing purposes.
- Clustering webpages based on their content (e.g., grouping internet articles).
- Grouping high/low risk patients based on their health characteristics for insurance policy planning.
Clustering Process
- Clustering learns by grouping data into sets of related clusters.
- Observations within each group are more similar to each other than observations within other groups.
Concept of Similarity
- Finding similarities between data based on the data characteristics.
- Similarity between two observations is measured as the distance between them.
Clustering Techniques
- Hierarchical method (e.g., Agglomerative clustering).
- Others (not specified in the text, but there are other clustering techniques like K-Means, K-Medoids, etc.).
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