Which domain can handle both structured and unstructured data and perform statistical operations to make a prediction?
Hadoop can handle large amounts of structured and unstructured data. Predictive analytics hardware and software, which process large amounts of complex data, and use machine learning and statistical algorithms to make predictions about future event outcomes.
What should be the order of data to apply CNN?
4. Layers in CNN
- Input layer.
- Convo layer (Convo + ReLU)
- Pooling layer.
- Fully connected(FC) layer.
- Softmax/logistic layer.
- Output layer.
How do you handle structured and unstructured data?
This means that structured data takes advantage of schema-on-write and unstructured data employs schema-on-read. Structured data is commonly stored in data warehouses and unstructured data is stored in data lakes….Structured data vs. unstructured data.
| Structured Data | Unstructured Data | |
|---|---|---|
| How | Predefined format | Native format |
Which of the following techniques help in reducing overfitting?
Dropout. It is another regularization technique that prevents neural networks from overfitting. Regularization methods like L1 and L2 reduce overfitting by modifying the cost function but on the contrary, the Dropout technique modifies the network itself to prevent the network from overfitting.
What are the prevalent method adopted for intrusion detection?
There are also two main approaches to detecting intrusion: signature-based IDS and anomaly-based IDS.
What is logistic regression in machine learning?
Logistic regression works well for cases where the dataset is linearly separable: A dataset is said to be linearly separable if it is possible to draw a straight line that can separate the two classes of data from each other.
What is binary logistic regression with example?
Binary logistic regression is the statistical technique used to predict the relationship between the dependent variable (Y) and the independent variable (X), where the dependent variable is binary in nature. For example, the output can be Success/Failure, 0/1, True/False, or Yes/No.
What is user database in logistic regression?
Prerequisite: Understanding Logistic Regression User Database – This dataset contains information of users from a companies database. It contains information about UserID, Gender, Age, EstimatedSalary, Purchased. We are using this dataset for predicting that a user will purchase the company’s newly launched product or not.
What is an independent variable in logistic regression?
Independent variables are those variables or factors which may influence the outcome (or dependent variable). So: Logistic regression is the correct type of analysis to use when you’re working with binary data.