उचित उदाहरण देते हुए फजान नियमों को लिखिए और समझाइए।
See Answer →असंगत इलेक्ट्रॉनिक विन्यास दशाने वाले परमाणुओं के कोई दो उदाहरण दीजिए।
See Answer →चार क्वांटम संख्याएँ कौन-सी हैं? उनकी सार्थकता बताइए।
See Answer →और की सार्थकता की व्याख्या कीजिए।
See Answer →श्रोडिंगर समीकरण के अनुप्रयोगों की सूची बनाइए।
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. प्रकाश-विद्युत् प्रभाव की संक्षिप्त चर्चा कीजिए। आइन्सटीन द्वारा इस प्रभाव की व्याख्या का भी वर्णन कीजिए।
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कण की द्वैती प्रकति के लिए दे-ब्रॉगली संबंध लिखिए। द्रव्य तरंगों को भी परिभाषित कीजिए।
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) हाइड्रोजन के परमाणु स्पेक्ट्रम में प्रदर्शित होने वाली विभिन्न रेखाओं के नाम बताइए ।
See Answer →उचित चित्र देते हुए गाइगर और मार्सडेन के प्रयोग की व्याख्या कीजिए।
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The following diagram represents a feed-forward neural network with one hidden layer:
The following diagram represents a feed-forward neural network with one hidden layer:
For the given points of two classes Blue and Yellow:
Blue: { (1,2), (2,3), (-1,2), (-1,4), (-1,-1)}
Yellow: { (4,2), (5,-1), (5,1), (6,1), (5,3)}
Plot a graph for the Blue and Yello categories. Find the support vectors and optimal separating line.
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Find a quadratic regressi on model for the following data. Use the regression model and calculate the value of Y at X = 9.
| X | 3 | 4 | 5 | 6 | 7 |
|---|---|---|---|---|---|
| Y | 2.5 | 3.2 | 3.8 | 6.5 | 11.5 |
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| Name | Hair | Height | Weight | Lotion | Result |
|---|---|---|---|---|---|
| Sarah | blonde | average | light | no | sunburned (positive) |
| Dana | blonde | tall | average | yes | none (negative) |
| Alex | brown | short | average | yes | none |
| Annie | blonde | short | average | no | sunburned |
| Emily | red | average | heavy | no | sunburned |
| Pete | brown | tall | heavy | no | none |
| John | brown | average | heavy | no | none |
| Katie | blonde | short | light | yes | none |
| Name | Hair | Height | Weight | Lotion | Result |
|---|---|---|---|---|---|
| Sarah | blonde | average | light | no | sunburned (positive) |
| Dana | blonde | tall | average | yes | none (negative) |
| Alex | brown | short | average | yes | none |
| Annie | blonde | short | average | no | sunburned |
| Emily | red | average | heavy | no | sunburned |
| Pete | brown | tall | heavy | no | none |
| John | brown | average | heavy | no | none |
| Katie | blonde | short | light | yes | none |
Use Naive Bayes classification method for the following dataset and classify the class (Species) of X = {Color=Green, Legs=2, Height=Tall, Smelly=No}
| Sl. No. | Color | Legs | Height | Smelly | Species |
|---|---|---|---|---|---|
| 1 | White | 3 | Short | Yes | M |
| 2 | Green | 2 | Tall | No | M |
| 3 | Green | 3 | Short | Yes | M |
| 4 | White | 3 | Short | Yes | M |
| 5 | Green | 2 | Short | No | H |
| 6 | White | 2 | Tall | No | H |
| 7 | White | 2 | Tall | No | H |
What is ensemble learning? Explain three primary classes of ensemble learning methods.
See Answer →For the following fuzzy sets:
A = {a/0.6, b/0.4, c/0.5, d/0.0, e/0.8}; B = {a/0.2, b/0.8, c/0.7, d/0.3, e/0.5}
C = {a/0.1, b/0.2, c/0.8, d/0.6, e/0.2}
Find the fuzzy sets: (i) A U B UC (ii) A ∩ B ∩ C (iii) A' U B' U C' (iv) A' ∩ B' ∩ C'
(v) (A ∩ B UC)'