The hierarchy of AI and Machine Learning
Declaring and instantiating a Naive Bayes classifier for multiple lables
What is nb= MultinomialNB()
Location of demonstrations on the scikit learn website
What is the Examples section?
Where DataFrame comes from
What is pandas?
Classification algorithm that uses the "best split"
What is the Decision Tree Classifier?
A type of ML where we are given data as an input and attempt to output the correct label
What is supervised learning?
Fitting your data to a classifier
What is
CLASSIFIER NAME.fit(x_train, y_train)
Scikit learn datasets we imported and utilized
What are the iris and breast cancer datasets?
What is numPy?
Datasets can lack representation and reflect ___
What is human bias?
When the lable is a specific class
What is classification?
What is train_test_split(x, y, test_size=??, random_state=??)?
Where you can find everything from the scikit learn package?
What is the API?
What is matplotlib?
What makes up the f1 score
What are precision and recall?
When the label is a real number
What is regression?
Order of outputs when splitting up train and test sets
What are x_train, x_test, y_train, y_test?
Importing scikit learn in python
What is import sklearn?
How we plotted the decision tree
What is graphviz?
A confusion matrix that has pretty colors is called a ___
What is a heatmap?
Uses probability to determine how likely an example belongs to a class, with an independence assumption
What is Naive Bayes Classification?
How to import the f1 score from scikit learn
What is from sklearn.metrics import f1_score?
How we got pretty colors on the confusion matrices
What is seaborn?
Bayes Theorem
What is the probability of B given that A = the probability of A given that B * the probability of B / the probability of A?