Bayes’ Theorem provides a way that we can calculate the probability of a piece of data belonging to a given class, given our prior knowledge.
P(class|data) = (P(data|class) * P(class)) / P(data)
Where P(class|data) is the probability of class given the provided data.
Explanation:
- Naive Bayes is a classification algorithm for binary and multiclass classification problems.
- It is called Naive Bayes or idiot Bayes because the calculations of the probabilities for each class are simplified to make their calculations tractable.
This Naive Bayes tutorial is broken down into 5 parts:
Step 1: Separate By Class : Calculate the probability of data by the class they belong to, the so-called base rate. Separate our training data by class.
Step 2: Summarize Dataset : The two statistics we require from a given dataset are the mean and the standard deviation
The mean is the average value and can be calculated using :
mean = sum(x)/n * count(x)
Step 3: Summarize Data By Class : Statistics from our training dataset organized by class.
Step 4: Gaussian Probability Density Function : Probability or likelihood of observing a given real-value. One way we can do this is to assume that the values are drawn from a distribution, such as a bell curve or Gaussian distribution.
Step 5: Class Probabilities : The statistics calculated from our training data to calculate probabilities for new data. Probabilities are calculated separately for each class. This means that we first calculate the probability that a new piece of data belongs to the first class, then calculate the second class, on for all the classes.
Answer:
1. Start
2. Display "Enter three numbers"
3. Input A
4. Input B
5. Input C
6. Sum = A + B + C
7. Display Sum
8. Stop
Explanation:
Line 1 and Line 7 of the algorithm implies the start and end of the algorithm, respectively.
Line 2 prompts user for input of three numbers
Line 3 to 5 accept input from user and these inputs are saved in variables A, B and C
Line 6 adds the three inputs and saves the result in variable Sum
Line 7 displays the value of Sum
Answer:
2. Scientists use seismometers to measure the earthquake activity that occurs beneath a volcano. They then predict the eruption of that volcano.
Explanation:
The options are:
1. Before a volcano erupts, earthquake activity beneath the volcano decreases.2. Scientists use seismometers to measure the earthquake activity that occurs beneath a volcano. They then predict the eruption of that volcano.3. When a volcano erupts, the amount of carbon dioxide and sulfur dioxide emitted decreases. 4.Scientists measure the amount of these gases to determine the amount of magma present in the volcanic reservoir.
The answer is certainly 2. as seismometers are being used to find out the details of the earthquake activities which occur inside a volcano. And with this information, the volcanologists then predict the eruption of that particular volcano. Hence, the 2nd option does not have any factual errors, and all the others have factual errors.