Association Rules Mining, Apriori Implimentation

Timothy Asp, Caleb Carlton

Input Format: python apriori.py [--no-rules] <dataFile-out1.csv> <minSup> <minConf> --no-rules will run the code without rules generation. The input datafile must be in the sparse vector format (see *-out1.csv in the different folders of ./data)

Example:

python apriori.py --no-rules data/1000/1000-out1.csv .03 .7 python apriori.py data/example/out1.csv .03 .7

== Extended Bakery Printouts

================================================================= Dataset: data/example/out1.csv MinSup: 0.03 MinConf: 0.7

1 : Blackberry Tart (15), Apple Danish (36) support= 0.139 2 : Gongolais Cookie (22), Napoleon Cake (9) support= 0.181 3 : Lemon Cake (1), Single Espresso (49) support= 0.127 4 : Apple Tart (12), Berry Tart (14), Blueberry Tart (16) support= 0.257

Skyline Itemsets: 4

Rule 1 : Blackberry Tart (15) --> Apple Danish (36) [sup= 0.139 conf= 0.751351351351 ] Rule 2 : Apple Danish (36) --> Blackberry Tart (15) [sup= 0.139 conf= 0.798850574713 ] Rule 3 : Gongolais Cookie (22) --> Napoleon Cake (9) [sup= 0.181 conf= 0.841860465116 ] Rule 4 : Napoleon Cake (9) --> Gongolais Cookie (22) [sup= 0.181 conf= 0.804444444444 ] Rule 5 : Lemon Cake (1) --> Single Espresso (49) [sup= 0.127 conf= 0.814102564103 ] Rule 6 : Single Espresso (49) --> Lemon Cake (1) [sup= 0.127 conf= 0.783950617284 ] Rule 7 : Apple Tart (12), Berry Tart (14) --> Blueberry Tart (16) [sup= 0.257 conf= 0.958955223881 ] Rule 8 : Apple Tart (12), Blueberry Tart (16) --> Berry Tart (14) [sup= 0.257 conf= 0.992277992278 ] Rule 9 : Berry Tart (14), Blueberry Tart (16) --> Apple Tart (12) [sup= 0.257 conf= 0.996124031008 ]

================================================================= Dataset: data/75000/75000-out1.csv MinSup: 0.033 MinConf: 0.7

1: Berry Tart (14), Bottled Water (44) support= 0.0378 2: Apricot Croissant (32), Hot Coffee (45) support= 0.0353733333333 3: Strawberry Cake (4), Napoleon Cake (9) support= 0.0431466666667 4: Casino Cake (2), Chocolate Coffee (46) support= 0.03524 5: Chocolate Tart (17), Vanilla Frappuccino (47) support= 0.03596 6: Marzipan Cookie (27), Tuile Cookie (28) support= 0.05092 7: Blackberry Tart (15), Coffee Eclair (7) support= 0.0364133333333 8: Blueberry Tart (16), Hot Coffee (45) support= 0.03504 9: Gongolais Cookie (22), Truffle Cake (5) support= 0.04392 10: Cheese Croissant (33), Orange Juice (42) support= 0.0430666666667 11: Blueberry Tart (16), Apricot Croissant (32) support= 0.0435066666667 12: Lemon Cake (1), Lemon Tart (19) support= 0.0368533333333 13: Chocolate Cake (0), Chocolate Coffee (46) support= 0.04404 14: Cherry Tart (18), Opera Cake (3), Apricot Danish (35) support= 0.0411066666667 15: Chocolate Coffee (46), Chocolate Cake (0), Casino Cake (2) support= 0.0333866666667 16: Apple Pie (11), Almond Twist (37), Coffee Eclair (7) support= 0.03432

Skyline Itemsets: 16

Rule 1: Cherry Tart (18), Opera Cake (3) --> Apricot Danish (35) [sup= 0.0411066666667 conf= 0.947740547187 ] Rule 2: Cherry Tart (18), Apricot Danish (35) --> Opera Cake (3) [sup= 0.0411066666667 conf= 0.77423405324 ] Rule 3: Opera Cake (3), Apricot Danish (35) --> Cherry Tart (18) [sup= 0.0411066666667 conf= 0.955376510691 ] Rule 4: Chocolate Cake (0), Casino Cake (2) --> Chocolate Coffee (46) [sup= 0.0333866666667 conf= 0.939587242026 ] Rule 5: Apple Pie (11), Almond Twist (37) --> Coffee Eclair (7) [sup= 0.03432 conf= 0.935659760087 ] Rule 6: Apple Pie (11), Coffee Eclair (7) --> Almond Twist (37) [sup= 0.03432 conf= 0.920930232558 ] Rule 7: Almond Twist (37), Coffee Eclair (7) --> Apple Pie (11) [sup= 0.03432 conf= 0.924568965517 ]

================================================================= Dataset: data/20000/20000-out1.csv MinSup: 0.03 MinConf: 0.7

1: Berry Tart (14), Bottled Water (44) support= 0.0357 2: Chocolate Tart (17), Walnut Cookie (29) support= 0.03055 3: Strawberry Cake (4), Napoleon Cake (9) support= 0.04455 4: Casino Cake (2), Chocolate Coffee (46) support= 0.0357 5: Almond Twist (37), Hot Coffee (45) support= 0.03085 6: Hot Coffee (45), Coffee Eclair (7) support= 0.0317 7: Blackberry Tart (15), Single Espresso (49) support= 0.03015 8: Chocolate Tart (17), Vanilla Frappuccino (47) support= 0.03675 9: Marzipan Cookie (27), Tuile Cookie (28) support= 0.04855 10: Blackberry Tart (15), Coffee Eclair (7) support= 0.03675 11: Blueberry Tart (16), Hot Coffee (45) support= 0.0357 12: Gongolais Cookie (22), Truffle Cake (5) support= 0.04335 13: Lemon Cake (1), Lemon Tart (19) support= 0.037 14: Cheese Croissant (33), Orange Juice (42) support= 0.0439 15: Apple Pie (11), Hot Coffee (45) support= 0.03085 16: Blueberry Tart (16), Apricot Croissant (32) support= 0.04185 17: Chocolate Cake (0), Chocolate Coffee (46) support= 0.04405 18: Walnut Cookie (29), Vanilla Frappuccino (47) support= 0.03095 19: Chocolate Coffee (46), Chocolate Cake (0), Casino Cake (2) support= 0.0339 20: Apricot Croissant (32), Hot Coffee (45), Blueberry Tart (16) support= 0.0326 21: Apple Pie (11), Almond Twist (37), Coffee Eclair (7) support= 0.03415 22: Cherry Tart (18), Opera Cake (3), Apricot Danish (35) support= 0.041

Skyline Itemsets: 22

Rule 1: Chocolate Cake (0), Casino Cake (2) --> Chocolate Coffee (46) [sup= 0.0339 conf= 0.945606694561 ] Rule 2: Apricot Croissant (32), Hot Coffee (45) --> Blueberry Tart (16) [sup= 0.0326 conf= 0.928774928775 ] Rule 3: Apple Pie (11), Almond Twist (37) --> Coffee Eclair (7) [sup= 0.03415 conf= 0.949930458971 ] Rule 4: Apple Pie (11), Coffee Eclair (7) --> Almond Twist (37) [sup= 0.03415 conf= 0.91677852349 ] Rule 5: Almond Twist (37), Coffee Eclair (7) --> Apple Pie (11) [sup= 0.03415 conf= 0.942068965517 ] Rule 6: Cherry Tart (18), Opera Cake (3) --> Apricot Danish (35) [sup= 0.041 conf= 0.939289805269 ] Rule 7: Cherry Tart (18), Apricot Danish (35) --> Opera Cake (3) [sup= 0.041 conf= 0.780209324453 ] Rule 8: Opera Cake (3), Apricot Danish (35) --> Cherry Tart (18) [sup= 0.041 conf= 0.945790080738 ]

================================================================== Dataset: data/5000/5000-out1.csv MinSup: 0.03 MinConf: 0.7

1: Strawberry Cake (4), Napoleon Cake (9) support= 0.0422 2: Casino Cake (2), Chocolate Coffee (46) support= 0.0346 3: Almond Twist (37), Hot Coffee (45) support= 0.0336 4: Blackberry Tart (15), Single Espresso (49) support= 0.0314 5: Chocolate Tart (17), Vanilla Frappuccino (47) support= 0.0348 6: Marzipan Cookie (27), Tuile Cookie (28) support= 0.0496 7: Apple Croissant (31), Apple Danish (36) support= 0.033 8: Apple Tart (12), Apple Danish (36) support= 0.0324 9: Blackberry Tart (15), Coffee Eclair (7) support= 0.0356 10: Blueberry Tart (16), Hot Coffee (45) support= 0.035 11: Gongolais Cookie (22), Truffle Cake (5) support= 0.0472 12: Lemon Cake (1), Lemon Tart (19) support= 0.0336 13: Cheese Croissant (33), Orange Juice (42) support= 0.043 14: Berry Tart (14), Bottled Water (44) support= 0.0366 15: Blueberry Tart (16), Apricot Croissant (32) support= 0.044 16: Chocolate Cake (0), Chocolate Coffee (46) support= 0.0394 17: Apple Tart (12), Apple Croissant (31) support= 0.0316 18: Chocolate Coffee (46), Chocolate Cake (0), Casino Cake (2) support= 0.0312 19: Apricot Croissant (32), Hot Coffee (45), Blueberry Tart (16) support= 0.0328 20: Cherry Tart (18), Opera Cake (3), Apricot Danish (35) support= 0.0408 21: Apple Pie (11), Hot Coffee (45), Almond Twist (37), Coffee Eclair (7) support= 0.0308

Skyline Itemsets: 21

Rule 1: Chocolate Cake (0), Casino Cake (2) --> Chocolate Coffee (46) [sup= 0.0312 conf= 0.912280701754 ] Rule 2: Apricot Croissant (32), Hot Coffee (45) --> Blueberry Tart (16) [sup= 0.0328 conf= 0.942528735632 ] Rule 3: Cherry Tart (18), Opera Cake (3) --> Apricot Danish (35) [sup= 0.0408 conf= 0.935779816514 ] Rule 4: Cherry Tart (18), Apricot Danish (35) --> Opera Cake (3) [sup= 0.0408 conf= 0.796875 ] Rule 5: Opera Cake (3), Apricot Danish (35) --> Cherry Tart (18) [sup= 0.0408 conf= 0.944444444444 ] Rule 6: Apple Pie (11), Hot Coffee (45), Almond Twist (37) --> Coffee Eclair (7) [sup= 0.0308 conf= 1.0 ] Rule 7: Apple Pie (11), Hot Coffee (45), Coffee Eclair (7) --> Almond Twist (37) [sup= 0.0308 conf= 1.0 ] Rule 8: Apple Pie (11), Almond Twist (37), Coffee Eclair (7) --> Hot Coffee (45) [sup= 0.0308 conf= 0.806282722513 ] Rule 9: Hot Coffee (45), Almond Twist (37), Coffee Eclair (7) --> Apple Pie (11) [sup= 0.0308 conf= 1.0 ]

================================================================== Dataset: data/1000/1000-out1.csv MinSup: 0.03 MinConf: 0.5

1: Berry Tart (14), Bottled Water (44) support= 0.034 2: Strawberry Cake (4), Napoleon Cake (9) support= 0.049 3: Chocolate Cake (0), Casino Cake (2) support=