Big data (f) are the conditional probabilities for the traning set (20 observations) (g) there are 3 new future data you
Posted: Thu Apr 28, 2022 7:33 am
Big data
(f) are the conditional probabilities for the traning set (20
observations)
(g) there are 3 new future data you want to predict
1 st one to preditct is Gender=male, type = lux, size=medium,
you predict what class(C0. C1)?
Consider the training examples shown in the following table for a binary classification problem. CID | Gender Type | Size | Class M M M 1 2 3 4 5 6 7 1 1 1 1 | 1 1 | 1 1 1 1 1 1 1 M M M F F F F M 8 9 10 11 12 13 14 15 16 17 18 19 20 1 Family Small 1 | Sports Medium 1 | Sports Medium 1 Sports | Large 1 | Sports | E Large | Sports E Large 1 1 Sports Small 1 1 Sports Small 1 | Sports Medium 1 1 Luxury | Large | Family Large 1 1 Family E Large Family Medium I Luxury | E Large 1 Luxury | Small 1 Luxury Small Luxury | Medium 1 Luxury | Medium 1 1 Luxury Medium 1 | Luxury | Large 1 CO CO CO CO CO CO CO CO CO CO C1 C1 C1 C1 C1 C1 C1 C1 C1 C1 M M M F F F F F F 1 |
L (1) Based on the given training date set, calculate the probabilities required for a Naïve Bayers classifier. Using Laplace smoothing for k=1 estimate to smooth the following probability estimates: P(C=CO) = ? P(C=C1)= ? P(G=MC=CO) = ? P(G=MC=C1) = ? P(G=F|C=CO) = ? P(G=F|C=C1) = ? P(T =F|C=CO) = ? P(T =F|C=C1)= ? P(T ES|C=CO) = ? P(T = |C=C1) = ? P(T =LC=C0) = ? P(T =L|C=C1)= P(S=S|C=CO) = ? P(S=S|C=C1) = ? P(S=M|C=CO) = ? P(S=M|C=C1) = ? P(SELİC=CO) = ? P(S=LIC=C1) = ? P(S=E|C=CO) = ? P(S=E|C=C1) = ? [18 marks) (g) Using your Naïve Bayers model with Laplace smoothing for k=1 estimate to classify the following three records. [3 marks] Gender Type Size M F F 2 LLLL | Luxury | Medium | Luxury | Large 1 Luxury | E Large
(f) are the conditional probabilities for the traning set (20
observations)
(g) there are 3 new future data you want to predict
1 st one to preditct is Gender=male, type = lux, size=medium,
you predict what class(C0. C1)?
- Big Data F Are The Conditional Probabilities For The Traning Set 20 Observations G There Are 3 New Future Data You 1 (45.16 KiB) Viewed 26 times
- Big Data F Are The Conditional Probabilities For The Traning Set 20 Observations G There Are 3 New Future Data You 2 (46.63 KiB) Viewed 26 times
L (1) Based on the given training date set, calculate the probabilities required for a Naïve Bayers classifier. Using Laplace smoothing for k=1 estimate to smooth the following probability estimates: P(C=CO) = ? P(C=C1)= ? P(G=MC=CO) = ? P(G=MC=C1) = ? P(G=F|C=CO) = ? P(G=F|C=C1) = ? P(T =F|C=CO) = ? P(T =F|C=C1)= ? P(T ES|C=CO) = ? P(T = |C=C1) = ? P(T =LC=C0) = ? P(T =L|C=C1)= P(S=S|C=CO) = ? P(S=S|C=C1) = ? P(S=M|C=CO) = ? P(S=M|C=C1) = ? P(SELİC=CO) = ? P(S=LIC=C1) = ? P(S=E|C=CO) = ? P(S=E|C=C1) = ? [18 marks) (g) Using your Naïve Bayers model with Laplace smoothing for k=1 estimate to classify the following three records. [3 marks] Gender Type Size M F F 2 LLLL | Luxury | Medium | Luxury | Large 1 Luxury | E Large