Find Interview Questions for Decisiontree analytics & services

Right Answer:
Supervised learning uses labeled data to train models, meaning the output is known, while unsupervised learning uses unlabeled data, where the model tries to find patterns or groupings without predefined outcomes.

Right Answer:
The different types of data distributions include:

1. Normal Distribution
2. Binomial Distribution
3. Poisson Distribution
4. Uniform Distribution
5. Exponential Distribution
6. Log-Normal Distribution
7. Geometric Distribution
8. Beta Distribution
9. Chi-Squared Distribution
10. Student's t-Distribution

Right Answer:
Outliers are data points that significantly differ from the rest of the dataset. They can skew results and affect statistical analyses. To handle outliers, you can:

1. Identify them using methods like the IQR (Interquartile Range) or Z-scores.
2. Remove them if they are errors or irrelevant.
3. Transform them using techniques like log transformation.
4. Use robust statistical methods that are less affected by outliers.
5. Analyze them separately if they provide valuable insights.

Right Answer:
Some common data visualization techniques include:

1. Bar Charts
2. Line Graphs
3. Pie Charts
4. Scatter Plots
5. Histograms
6. Heat Maps
7. Box Plots
8. Area Charts
9. Tree Maps
10. Bubble Charts

Right Answer:
To handle missing data in a dataset, you can use the following methods:

1. **Remove Rows/Columns**: Delete rows or columns with missing values if they are not significant.
2. **Imputation**: Fill in missing values using techniques like mean, median, mode, or more advanced methods like KNN or regression.
3. **Flagging**: Create a new column to indicate missing values for analysis.
4. **Predictive Modeling**: Use algorithms to predict and fill in missing values based on other data.
5. **Leave as Is**: In some cases, you may choose to leave missing values if they are meaningful for analysis.

Right Answer:
OLAP (Online Analytical Processing) is used for analyzing large volumes of data for reporting and decision-making, while OLTP (Online Transaction Processing) is used for managing day-to-day transactional data and operations.

Right Answer:
A transaction isolation level defines the degree to which the operations in one transaction are isolated from those in other concurrent transactions. The advantages include controlling data consistency and preventing issues like dirty reads, non-repeatable reads, and phantom reads.

The different options for transaction isolation levels in SQL Server are:

1. **Read Uncommitted**: Allows dirty reads.
2. **Read Committed**: Prevents dirty reads; only committed data is read.
3. **Repeatable Read**: Prevents dirty reads and non-repeatable reads; ensures that if a row is read twice, it will return the same data.
4. **Serializable**: Prevents dirty reads, non-repeatable reads, and phantom reads; ensures complete isolation by locking the range of rows.
5. **Snapshot**: Provides a view of the data as it was at the start of the transaction, preventing locks and allowing for consistent reads.

Right Answer:
The `del()` statement removes an item at a specific index from a list, while the `remove()` method removes the first occurrence of a specified value from the list.