PR Project Report

8/10/2019 PR Project Report

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PATTERN RECOGNITION ASSIGNMENT

Submitted by HARI NARAYAN N.U

B110490EE

EEE A batch

TRAINING DATA

=== Run information ===

Scheme:weka.classifiers.bayes.NaiveBayes

Relation: haberman-weka.filters.unsupervised.instance.RemovePercentage-P50.0-V

Instances: 153

Attributes: 4

Age_of_patient_at_time_of_operation

Patients_year_of_operation

Number_of_positive_axillary_nodes_detected

Survival_status

Test mode:evaluate on training data

=== Classifier model (full training set) ===

Naive Bayes Classifier

Class

Attribute 1 2

(0.74) (0.26)

=============================================================



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mean 43.0259 45.3968

std. dev. 6.1537 4.7468

weight sum 114 39

precision 1.0476 1.0476


58 12.0 6.0

59 12.0 7.0

60 17.0 2.0

61 13.0 1.0

62 10.0 4.0

63 15.0 5.0

64 11.0 7.0

65 10.0 4.0

66 10.0 5.0

67 9.0 4.0

68 3.0 1.0

69 4.0 5.0

[total] 126.0 51.0


mean 2.7161 7.3333

std. dev. 4.8927 10.2232

weight sum 114 39

precision 2.3636 2.3636

Time taken to build model: 0 seconds


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=== Evaluation on training set ===

=== Summary ===

Correctly Classified Instances 119 77.7778 %

Incorrectly Classified Instances 34 22.2222 %

Kappa statistic 0.2817

Mean absolute error 0.2806

Root mean squared error 0.403

Relative absolute error 73.5784 %

Root relative squared error 92.4707 %

Total Number of Instances 153

=== Detailed Accuracy By Class ===

TP Rate FP Rate Precision Recall F-Measure ROC Area Class

0.947 0.718 0.794 0.947 0.864 0.791 1

0.282 0.053 0.647 0.282 0.393 0.791 2

Weighted Avg. 0.778 0.548 0.757 0.778 0.744 0.791

=== Confusion Matrix ===

a b


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TEST DATA


Scheme:weka.classifiers.bayes.NaiveBayes

Relation: haberman-weka.filters.unsupervised.instance.RemovePercentage-P50.0-V

Instances: 153

Attributes: 4




Survival_status

Test mode:user supplied test set: size unknown (reading incrementally)


Naive Bayes Classifier

Class

Attribute 1 2

(0.74) (0.26)

=============================================================


mean 43.0259 45.3968

std. dev. 6.1537 4.7468

weight sum 114 39


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precision 1.0476 1.0476


58 12.0 6.0

59 12.0 7.0

60 17.0 2.0

61 13.0 1.0

62 10.0 4.0

63 15.0 5.0

64 11.0 7.0

65 10.0 4.0

66 10.0 5.0

67 9.0 4.0

68 3.0 1.0

69 4.0 5.0

[total] 126.0 51.0


mean 2.7161 7.3333

std. dev. 4.8927 10.2232

weight sum 114 39

precision 2.3636 2.3636


=== Evaluation on test set ===

=== Summary ===


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0.937 0.762 0.765 0.937 0.842 0.591 1

0.238 0.063 0.588 0.238 0.339 0.591 2

Weighted Avg. 0.745 0.57 0.716 0.745 0.704 0.591


a b


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NEAREST NEIGHBOUR CLASSIFICATION


Scheme:weka.classifiers.lazy.IBk -K 7 -W 0 -A "weka.core.neighboursearch.LinearNNSearch -A

\"weka.core.EuclideanDistance -R first-last\""

Relation: haberman

Instances: 306

Attributes: 4




Survival_status

Test mode:user supplied test set: size unknown (reading incrementally)


IB1 instance-based classifier

using 7 nearest neighbour(s) for classification


=== Evaluation on test set ===

=== Summary ===





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0.946 0.643 0.795 0.946 0.864 0.801 1

0.357 0.054 0.714 0.357 0.476 0.801 2

Weighted Avg. 0.784 0.481 0.773 0.784 0.758 0.801


a b


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K MEAN CLUSTERING


Scheme:weka.clusterers.SimpleKMeans -N 4 -A "weka.core.EuclideanDistance -R first-last" -I 500 -S 10

Relation: haberman

Instances: 306

Attributes: 4




Ignored:

Survival_status

Test mode:Classes to clusters evaluation on training data

=== Model and evaluation on training set ===

kMeans

======

Number of iterations: 6

Within cluster sum of squared errors: 197.29360453534517

Missing values globally replaced with mean/mode

Cluster centroids:

Cluster#

Attribute Full Data 0 1 2 3

(306) (52) (89) (87) (78)


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=====================================================================================

==============

Age_of_patient_at_time_of_operation 52.4575 56.3462 59.618 43.8506 51.2949

Patients_year_of_operation 58 67 58 63 64

Number_of_positive_axillary_nodes_detected 4.0261 10.1731 2.3034 4.1494 1.7564

Time taken to build model (full training data) : 0.02 seconds

=== Model and evaluation on training set ===

Clustered Instances

0 52 ( 17%)

1 89 ( 29%)

2 87 ( 28%)

3 78 ( 25%)

Class attribute: Survival_status

Classes to Clusters:

0 1 2 3


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Cluster 1


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Sample Clusters


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2.PROBLEM 2


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Documents

PR Project Report