Created
October 26, 2020 13:26
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Naive Bayes Classifier Implementation
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| testData = "Type Long NotLong Sweet NotSweet Yellow NotYellow Total\nBanana 400 100 350 150 450 50 500\nOrange 0 300 150 150 300 0 300\nOther 100 100 150 50 50 150 200\nTotal 500 500 650 350 800 200 1000" | |
| file = open("data.txt", "w+") | |
| file.write(testData) | |
| file.close() | |
| file = open("data.txt", "r") | |
| lines = file.readlines() | |
| file.close() | |
| types = ['long', 'notlong', 'sweet', 'notsweet', 'yellow', 'notyellow', 'total'] | |
| dataset = {} | |
| for line in lines[1:]: | |
| data = line.replace('\n', '').split(' ') | |
| dataset[data[0].lower()] = {} | |
| d = data[1:] | |
| for idx, type in enumerate(types): | |
| dataset[data[0].lower()][type] = int(d[idx]) | |
| def calcP(obj, idx, div=None): | |
| if not div: | |
| div = dataset[obj]['total'] | |
| return dataset[obj][idx] / div | |
| def naiveBayes(pAB, pA, pB): | |
| nB = (pAB * pB) / pA | |
| return nB if nB <= 1.0 else 1.0 | |
| pTypes = {} | |
| for type in types: | |
| pTypes[type] = calcP('total', type) | |
| pFruits = {} | |
| for fruit in dataset: | |
| pFruits[fruit] = calcP(fruit, 'total', dataset['total'][type]) | |
| pFruitType = {} | |
| for fruit in dataset: | |
| pFruitType[fruit] = {} | |
| for idx, type in enumerate(types): | |
| pFruitType[fruit][type] = calcP(fruit, type, dataset['total'][type]) | |
| pTypeFruit = {} | |
| for type in types: | |
| pTypeFruit[type] = {} | |
| for fruit in dataset: | |
| pTypeFruit[type][fruit] = naiveBayes(pFruitType[fruit][type], pFruits[fruit], pTypes[type]) | |
| pFruitProbability = {} | |
| classifyBy = ['sweet', 'notlong', 'yellow'] # [set(input("Enter types of the unknown fruit: ").split(' ')] | |
| for fruit in dataset: | |
| pFruitProbability[fruit] = 1 | |
| for cls in classifyBy: | |
| pFruitProbability[fruit] *= pTypeFruit[cls][fruit] # * pTypeFruit['sweet'][fruit] * pTypeFruit['yellow'][fruit] | |
| decession = max(pFruitProbability, key=pFruitProbability.get) | |
| print(f"The class of an unknown fruit that is {', '.join(classifyBy)} is '{decession}'") |
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