reference_contingency7
py
Inner variable: sepal length
Outer variable: iris
Class variable: iris
Attribute: sepal length
Distributions:
p(.|Iris-setosa) = <4.300: 0.020, 4.400: 0.060, 4.500: 0.020, 4.600: 0.080, 4.700: 0.040, 4.800: 0.100, 4.900: 0.080, 5.000: 0.160, 5.100: 0.160, 5.200: 0.060, 5.300: 0.020, 5.400: 0.100, 5.500: 0.040, 5.700: 0.040, 5.800: 0.020>
p(.|Iris-versicolor) = <4.900: 0.020, 5.000: 0.040, 5.100: 0.020, 5.200: 0.020, 5.400: 0.020, 5.500: 0.100, 5.600: 0.100, 5.700: 0.100, 5.800: 0.060, 5.900: 0.040, 6.000: 0.080, 6.100: 0.080, 6.200: 0.040, 6.300: 0.060, 6.400: 0.040, 6.500: 0.020, 6.600: 0.040, 6.700: 0.060, 6.800: 0.020, 6.900: 0.020, 7.000: 0.020>
p(.|Iris-virginica) = <4.900: 0.020, 5.600: 0.020, 5.700: 0.020, 5.800: 0.060, 5.900: 0.020, 6.000: 0.040, 6.100: 0.040, 6.200: 0.040, 6.300: 0.120, 6.400: 0.100, 6.500: 0.080, 6.700: 0.100, 6.800: 0.040, 6.900: 0.060, 7.100: 0.020, 7.200: 0.060, 7.300: 0.020, 7.400: 0.020, 7.600: 0.020, 7.700: 0.080, 7.900: 0.020>
Probabilities for e=5.5
p(5.5|Iris-setosa) = 2.000
p(5.5|Iris-versicolor) = 5.000
p(5.5|Iris-virginica) = 1.000
Distributions from a matrix computed manually:
p(.|Iris-setosa) = <4.300: 0.020, 4.400: 0.060, 4.500: 0.020, 4.600: 0.080, 4.700: 0.040, 4.800: 0.100, 4.900: 0.080, 5.000: 0.160, 5.100: 0.160, 5.200: 0.060, 5.300: 0.020, 5.400: 0.100, 5.500: 0.040, 5.700: 0.040, 5.800: 0.020>
p(.|Iris-versicolor) = <4.900: 0.020, 5.000: 0.040, 5.100: 0.020, 5.200: 0.020, 5.400: 0.020, 5.500: 0.100, 5.600: 0.100, 5.700: 0.100, 5.800: 0.060, 5.900: 0.040, 6.000: 0.080, 6.100: 0.080, 6.200: 0.040, 6.300: 0.060, 6.400: 0.040, 6.500: 0.020, 6.600: 0.040, 6.700: 0.060, 6.800: 0.020, 6.900: 0.020, 7.000: 0.020>
p(.|Iris-virginica) = <4.900: 0.020, 5.600: 0.020, 5.700: 0.020, 5.800: 0.060, 5.900: 0.020, 6.000: 0.040, 6.100: 0.040, 6.200: 0.040, 6.300: 0.120, 6.400: 0.100, 6.500: 0.080, 6.700: 0.100, 6.800: 0.040, 6.900: 0.060, 7.100: 0.020, 7.200: 0.060, 7.300: 0.020, 7.400: 0.020, 7.600: 0.020, 7.700: 0.080, 7.900: 0.020>