Answer:
Number 1 would be the answer and most safest one to choose.
Answer:
That it
Explanation:
There have been mass extinctions during the Cenozoic as there were during the Mesozoic and Paleozoic, but not as many animals and plants have disappeared. Finally, humanity appeared during the last two million years.The human lineage only diverged from our most recent common ancestor about 5 million years ago; less than half of 1% of that time, and modern Homo sapiens is only between 200,000 and 50,000 years old, depending on your definition.
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.
