As a highly flexible structure, a <u>matrix organization</u> can be quickly configured to adapt as required due to changes.
<h3>What is a matrix organizational structure?</h3>
A matrix organizational structure can be defined as a type of work structure where reporting relationships between employees and the top executive (employers) are set up as a matrix rather than the conventional hierarchy approach, which makes it highly flexible and adaptable to subsequent changes.
<h3>The types of matrix organizational structure.</h3>
In business management, there are three types of matrix organizational structure and these include:
- Balanced matrix structure.
Read more on matrix organization here: brainly.com/question/7437866
Answer:
A driver assists with hardware management.
Hope this helped.
Answer: the answer is A.
Explanation: hope this helps!
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:
wertweabcd
Explanation:
The LPAD() function left-pads a string with another string, to a certain length.
LPAD(string, length, lpad_string)
Parameter Description
string: Required. The original string. If the length of the original string is larger than the length parameter, this function removes the overfloating characters from string
length: Required. The length of the string after it has been left-padded
lpad_string: Required. The string to left-pad to string.
In example;
SELECT LPAD("SQL Brainly", 20, "ABC");
Output : ABCABCABSQL Brainly