1 00:00:00,266 --> 00:00:01,233 All right, my friends. 2 00:00:01,233 --> 00:00:02,466 Are you ready to. 3 00:00:02,466 --> 00:00:05,100 Train your primary model on the whole. 4 00:00:05,100 --> 00:00:06,300 Data set? 5 00:00:06,300 --> 00:00:07,833 Well, I bet you are. 6 00:00:07,833 --> 00:00:10,333 Because, indeed, we actually did. The most. 7 00:00:10,333 --> 00:00:13,000 Difficult. Parts. You know, the most. Difficult part was to. 8 00:00:13,000 --> 00:00:17,366 Make that transaction's list containing all the different transactions of our. 9 00:00:17,400 --> 00:00:18,000 Data set. 10 00:00:18,000 --> 00:00:21,500 You know, to 7501 transactions. 11 00:00:21,733 --> 00:00:22,333 We all. 12 00:00:22,333 --> 00:00:25,800 Put them into this transactions list with strings for. 13 00:00:25,800 --> 00:00:26,933 Each of the products. 14 00:00:26,933 --> 00:00:28,500 And this transactions list. 15 00:00:28,500 --> 00:00:31,233 Will be the input of the primary. 16 00:00:31,233 --> 00:00:35,766 Function, which we will use right now to train the primary model on this data set. 17 00:00:36,000 --> 00:00:37,633 And so that's what I'm talking about. 18 00:00:37,633 --> 00:00:38,400 Most of. 19 00:00:38,400 --> 00:00:40,833 The job. Is done because now the only thing that we. 20 00:00:40,833 --> 00:00:43,066 Have to do is just call this primary. 21 00:00:43,066 --> 00:00:45,933 Function from this a. Binary package. 22 00:00:45,933 --> 00:00:50,133 Which we installed in the first cell and call that function with some relevant. 23 00:00:50,133 --> 00:00:52,100 Values of the. Parameters. 24 00:00:52,100 --> 00:00:54,200 And that will be most of the. 25 00:00:54,200 --> 00:00:56,966 Reflection will have when building and training this. 26 00:00:56,966 --> 00:00:59,500 Apriori. Model. All right. Are you ready? 27 00:00:59,500 --> 00:01:00,400 Let's do this. 28 00:01:00,400 --> 00:01:03,200 Let's create a new code cell. 29 00:01:03,200 --> 00:01:08,633 So the first thing to do will be to import effectively that a primary function. 30 00:01:08,633 --> 00:01:11,533 Because so far. Make sure to understand that we. 31 00:01:11,533 --> 00:01:14,400 Only installed the primary package but we. 32 00:01:14,400 --> 00:01:16,133 Haven't imported anything. 33 00:01:16,133 --> 00:01:20,400 The only libraries we import were numpy, matplotlib and pandas. 34 00:01:20,566 --> 00:01:21,333 So now we need. 35 00:01:21,333 --> 00:01:24,433 Indeed to upload this a primary. 36 00:01:24,433 --> 00:01:26,966 Function. And this primary function belongs. 37 00:01:26,966 --> 00:01:30,066 To the binary package which we installed first. 38 00:01:30,233 --> 00:01:30,933 Therefore we need to. 39 00:01:30,933 --> 00:01:32,566 Start. From. 40 00:01:32,566 --> 00:01:35,566 That a binary package. 41 00:01:35,666 --> 00:01:36,900 There you go from. 42 00:01:36,900 --> 00:01:38,666 Which we import. 43 00:01:38,666 --> 00:01:41,666 That a primary function. All right. 44 00:01:41,966 --> 00:01:43,933 There we go again a primary. 45 00:01:43,933 --> 00:01:46,933 And now now we can call that function. 46 00:01:47,100 --> 00:01:47,366 All right. 47 00:01:47,366 --> 00:01:49,833 So first thing to understand is that this function will. 48 00:01:49,833 --> 00:01:51,766 Actually return the rules. 49 00:01:51,766 --> 00:01:55,033 You know not only will train the primary model on the data. 50 00:01:55,033 --> 00:01:55,966 Set, but also at. 51 00:01:55,966 --> 00:01:58,100 The same time this function will indeed train 52 00:01:58,100 --> 00:02:01,500 this primary model and in the end return the final rules, 53 00:02:01,500 --> 00:02:04,700 you know, with the different supports, confidences and lifts. 54 00:02:04,966 --> 00:02:06,366 And therefore, since we're now. 55 00:02:06,366 --> 00:02:08,400 Ready to call. This function, and since. 56 00:02:08,400 --> 00:02:12,200 This function returns the rules, well, let's create a new variable here 57 00:02:12,300 --> 00:02:14,833 which we're simply. Going to. Call rules. 58 00:02:14,833 --> 00:02:15,300 All right. 59 00:02:15,300 --> 00:02:18,300 And that will be the output of that function. 60 00:02:18,300 --> 00:02:20,066 And speaking of that function well let's. 61 00:02:20,066 --> 00:02:22,433 Call it. Right now. A priori. 62 00:02:22,433 --> 00:02:23,600 That's the function. 63 00:02:23,600 --> 00:02:25,766 Therefore I'm adding some parentheses. 64 00:02:25,766 --> 00:02:26,966 And now there we go. 65 00:02:26,966 --> 00:02:29,966 Let's see what parameters we have to input. 66 00:02:30,533 --> 00:02:30,866 All right. 67 00:02:30,866 --> 00:02:35,733 So this function takes as input some very intuitive arguments. 68 00:02:35,733 --> 00:02:38,533 We could actually you know almost guess all of them. 69 00:02:38,533 --> 00:02:39,600 The first one is of course. 70 00:02:39,600 --> 00:02:41,700 Well the data sets. You know, the. Data set. 71 00:02:41,700 --> 00:02:44,400 On which you're going to train your. A priori. Model. 72 00:02:44,400 --> 00:02:47,266 And the name for that parameter is transactions. 73 00:02:47,266 --> 00:02:49,933 Actually, you know. Because the. Primary model is. 74 00:02:49,933 --> 00:02:51,600 Mostly used to. 75 00:02:51,600 --> 00:02:54,466 Compute some correlations and association. Rules. 76 00:02:54,466 --> 00:02:56,000 Among transactions. 77 00:02:56,000 --> 00:02:58,500 So that's actually the name of the parameter. 78 00:02:58,500 --> 00:02:59,566 And of course the value. 79 00:02:59,566 --> 00:03:01,533 For that parameter must. Be well that. 80 00:03:01,533 --> 00:03:03,600 Same transactions. 81 00:03:03,600 --> 00:03:06,266 List which we created. 82 00:03:06,266 --> 00:03:07,666 In the right format. 83 00:03:07,666 --> 00:03:09,633 Right before this tutorial. In the. 84 00:03:09,633 --> 00:03:11,033 Data preprocessing phase. 85 00:03:11,033 --> 00:03:12,900 Okay. So this is the name of the parameter. 86 00:03:12,900 --> 00:03:14,966 And this is the name of our transactions. 87 00:03:14,966 --> 00:03:17,966 List which is the value of that parameter. 88 00:03:18,366 --> 00:03:20,400 Okay. Good. So that's for the first argument. 89 00:03:20,400 --> 00:03:21,866 That was an obvious one. 90 00:03:21,866 --> 00:03:22,466 And now. 91 00:03:22,466 --> 00:03:24,233 According to you what would. 92 00:03:24,233 --> 00:03:26,233 Be the next argument. 93 00:03:26,233 --> 00:03:27,866 Well, the next argument has to do. 94 00:03:27,866 --> 00:03:29,200 With the support. 95 00:03:29,200 --> 00:03:30,133 Of course, it's 96 00:03:30,133 --> 00:03:34,400 not going to be a simple support because we have a support for each rule. 97 00:03:34,500 --> 00:03:37,333 But what we can set is actually. 98 00:03:37,333 --> 00:03:40,900 A minimum support, you know, in order not to compute. 99 00:03:40,900 --> 00:03:43,800 All the rules, but only the rules that have at least. 100 00:03:43,800 --> 00:03:45,300 Some certain relevance. 101 00:03:45,300 --> 00:03:46,700 And therefore we will. 102 00:03:46,700 --> 00:03:49,200 Set a minimum support. Value. 103 00:03:49,200 --> 00:03:50,300 In order to take not. 104 00:03:50,300 --> 00:03:53,400 All the rules, but only the rules that have a support higher. 105 00:03:53,400 --> 00:03:55,500 Than this minimum. Support. 106 00:03:55,500 --> 00:03:57,633 All right. So let's first. Enter the name of the. 107 00:03:57,633 --> 00:03:58,633 Parameter here, which. 108 00:03:58,633 --> 00:04:00,900 Is min underscore. 109 00:04:00,900 --> 00:04:03,433 Support. Right. 110 00:04:03,433 --> 00:04:04,033 And now. 111 00:04:04,033 --> 00:04:06,600 According to you what should we choose. 112 00:04:06,600 --> 00:04:08,400 As a minimum support. Here. 113 00:04:08,400 --> 00:04:11,700 Well this has to do of course with our situation. 114 00:04:11,700 --> 00:04:15,066 You know the problem itself and of course some common sense. 115 00:04:15,400 --> 00:04:16,733 So let's recap. 116 00:04:16,733 --> 00:04:21,366 We have in total 7501 transactions. 117 00:04:21,366 --> 00:04:24,366 That were recorded over. One full week. 118 00:04:24,466 --> 00:04:29,866 And among these 7501 transactions, we want to get the most relevant rules. 119 00:04:29,866 --> 00:04:33,866 You know, the were, you know, the. 120 00:04:33,866 --> 00:04:35,533 Strongest rules of two. 121 00:04:35,533 --> 00:04:38,866 Elements, you know, with one element of the left hand side of the rule, 122 00:04:38,866 --> 00:04:41,966 you know, one product and one element in the right hand side of the. 123 00:04:41,966 --> 00:04:43,833 Rule, which is another product. 124 00:04:43,833 --> 00:04:46,000 And we want. Therefore, these products to. 125 00:04:46,000 --> 00:04:47,733 Appear a minimum amount of time. 126 00:04:47,733 --> 00:04:50,200 And that's exactly what the support is about. 127 00:04:50,200 --> 00:04:51,300 Remember the support. 128 00:04:51,300 --> 00:04:53,400 Of a couple of products A and B. 129 00:04:53,400 --> 00:04:55,966 Is the number of transactions containing. 130 00:04:55,966 --> 00:04:56,433 These two. 131 00:04:56,433 --> 00:04:57,500 Products A and B. 132 00:04:57,500 --> 00:04:58,666 Divided by the total. 133 00:04:58,666 --> 00:05:00,600 Number of transactions. 134 00:05:00,600 --> 00:05:02,000 So we need to see here. 135 00:05:02,000 --> 00:05:02,700 You know, for. 136 00:05:02,700 --> 00:05:04,500 A couple of products A and B. 137 00:05:04,500 --> 00:05:06,500 How many tons per. Week. 138 00:05:06,500 --> 00:05:08,300 We need to have at. Least these two products. 139 00:05:08,300 --> 00:05:09,866 In the transactions. 140 00:05:09,866 --> 00:05:12,366 Well you know. Let's. Do some common sense. 141 00:05:12,366 --> 00:05:15,333 Let's say that each day we would like to consider 142 00:05:15,333 --> 00:05:18,366 the products that appear in at least three. 143 00:05:18,433 --> 00:05:20,366 Transactions in the day. 144 00:05:20,366 --> 00:05:20,700 All right. 145 00:05:20,700 --> 00:05:21,966 Three transactions in a day. 146 00:05:21,966 --> 00:05:24,066 Because all the products that appear. 147 00:05:24,066 --> 00:05:27,166 In only one transaction or two transactions, you know, 148 00:05:27,166 --> 00:05:31,000 are actually not frequent, and we would not build some strong rules. 149 00:05:31,200 --> 00:05:32,466 Out of these products. 150 00:05:32,466 --> 00:05:34,000 So our common sense here. 151 00:05:34,000 --> 00:05:35,400 Is to. Only consider the. 152 00:05:35,400 --> 00:05:37,333 Products that appear at least. 153 00:05:37,333 --> 00:05:38,833 Three times a day. 154 00:05:38,833 --> 00:05:39,766 And therefore. 155 00:05:39,766 --> 00:05:43,133 Since the 7501 transactions. 156 00:05:43,133 --> 00:05:45,266 Were recorded. During the full. Week. 157 00:05:45,266 --> 00:05:48,100 Well, we need to multiply this number of three transactions. 158 00:05:48,100 --> 00:05:48,966 Per day by. 159 00:05:48,966 --> 00:05:52,566 Seven in order to get, you know, that minimum number of times. 160 00:05:52,566 --> 00:05:55,566 We want to see these products in the transactions per week. 161 00:05:55,633 --> 00:05:59,566 And therefore that number of times is three times seven equals 21. 162 00:05:59,833 --> 00:06:01,766 And since the. Support is. 163 00:06:01,766 --> 00:06:03,233 The number of times the. Products. 164 00:06:03,233 --> 00:06:06,866 Appear in the transactions divided by the total number of transactions. 165 00:06:07,000 --> 00:06:09,066 Well. The minimum. Support. 166 00:06:09,066 --> 00:06:11,366 Considering that we want to see minimum three times. 167 00:06:11,366 --> 00:06:13,733 Per day, the products must be. 168 00:06:13,733 --> 00:06:14,900 Three times seven. 169 00:06:14,900 --> 00:06:17,900 Divided by. 7000 and 501. 170 00:06:17,966 --> 00:06:18,266 All right. 171 00:06:18,266 --> 00:06:19,533 So that's purely. 172 00:06:19,533 --> 00:06:20,900 Based on common sense. 173 00:06:20,900 --> 00:06:22,966 You could choose another minimum support. 174 00:06:22,966 --> 00:06:24,866 But there you go. That's the minimum support. 175 00:06:24,866 --> 00:06:26,700 That goes well with our scenario. 176 00:06:26,700 --> 00:06:29,033 You know with our business. Case study. 177 00:06:29,033 --> 00:06:31,466 And therefore what I'm simply going to do now. 178 00:06:31,466 --> 00:06:35,166 Is just open a new tab here to quickly compute. 179 00:06:35,300 --> 00:06:38,100 Well, three as. In minimum three times one. 180 00:06:38,100 --> 00:06:40,900 To see the products appear. In the transactions per. Day. 181 00:06:40,900 --> 00:06:43,066 Then times seven. 182 00:06:43,066 --> 00:06:46,200 Because. The 7501 transactions are. 183 00:06:46,333 --> 00:06:47,800 Recorded over a week. 184 00:06:47,800 --> 00:06:49,833 And therefore, when calculating the support 185 00:06:49,833 --> 00:06:52,033 and dividing by the total number of transactions, 186 00:06:52,033 --> 00:06:53,833 the numerator and the denominator 187 00:06:53,833 --> 00:06:57,866 must be in the same unit of time, which is one week, and then divided. 188 00:06:57,866 --> 00:06:58,833 By seven. 189 00:06:58,833 --> 00:07:01,133 Thousand 501. 190 00:07:01,133 --> 00:07:02,666 Total. Transactions. 191 00:07:02,666 --> 00:07:03,233 There's just press. 192 00:07:03,233 --> 00:07:03,866 Enter. 193 00:07:03,866 --> 00:07:06,300 We'll get the result which is oh point. 194 00:07:06,300 --> 00:07:08,100 Oh 27. 195 00:07:08,100 --> 00:07:11,100 And we can round that up to 0.03. 196 00:07:11,266 --> 00:07:15,233 And 0.03 will be exactly our minimum support. 197 00:07:15,633 --> 00:07:16,833 So I'm going to close this. 198 00:07:16,833 --> 00:07:17,700 And I'm going to enter. 199 00:07:17,700 --> 00:07:20,800 Here 0.003. 200 00:07:21,333 --> 00:07:24,333 Perfect. So that's for. Our minimum support. 201 00:07:24,433 --> 00:07:26,600 Now the next argument what do you think. 202 00:07:26,600 --> 00:07:27,433 It's going to be. 203 00:07:27,433 --> 00:07:29,633 Well you probably guess that this. 204 00:07:29,633 --> 00:07:33,333 Time we're going to choose a minimum confidence. 205 00:07:33,766 --> 00:07:36,566 Right. A minimum confidence. 206 00:07:36,566 --> 00:07:39,000 All right. So this time what. Should we set. 207 00:07:39,000 --> 00:07:40,433 As the minimum confidence. 208 00:07:40,433 --> 00:07:43,066 Should we use. Again common sense. Or should we. 209 00:07:43,066 --> 00:07:44,666 Try some different values. 210 00:07:44,666 --> 00:07:48,333 Well this time we won't do the same kind of calculation as we did for the support. 211 00:07:48,700 --> 00:07:51,600 This time I'm rather going to give you some rule of sums. 212 00:07:51,600 --> 00:07:54,600 You know, which you can try when doing association rule learning. 213 00:07:54,933 --> 00:07:55,833 So I. 214 00:07:55,833 --> 00:07:58,133 Know from the other packages, you know the one from. 215 00:07:58,133 --> 00:07:59,700 R, because there is actually. 216 00:07:59,700 --> 00:08:02,666 A great function in. Order to do association. Learning. 217 00:08:02,666 --> 00:08:04,800 And it. Has indeed a default value. 218 00:08:04,800 --> 00:08:07,733 For the minimum confidence. Which is 0.8. 219 00:08:07,733 --> 00:08:10,200 So what I actually. Did, you know, for this problem. 220 00:08:10,200 --> 00:08:14,066 Is to start first with 0.8, but this was way too high 221 00:08:14,066 --> 00:08:17,366 because 0.88 would require the rule to be correct 80. 222 00:08:17,366 --> 00:08:18,400 Percent of the time. 223 00:08:18,400 --> 00:08:21,066 And therefore I ended up with actually no rule. 224 00:08:21,066 --> 00:08:23,433 So I had to reduce the confidence. 225 00:08:23,433 --> 00:08:25,333 So I. Divided by two so. 226 00:08:25,333 --> 00:08:28,333 That I can try a minimum confidence of 0.4. 227 00:08:28,400 --> 00:08:30,400 But still I got very few rules. 228 00:08:30,400 --> 00:08:32,333 And so I divided by two again. 229 00:08:32,333 --> 00:08:32,700 And this. 230 00:08:32,700 --> 00:08:35,933 With 0.2, I actually got. Some. Great rules. 231 00:08:35,933 --> 00:08:38,800 You know, not too much, not too. Few, but a. Dozen of them. 232 00:08:38,800 --> 00:08:39,900 So that was a good choice. 233 00:08:39,900 --> 00:08:40,300 And that's. 234 00:08:40,300 --> 00:08:41,933 How I chose. This minimum. 235 00:08:41,933 --> 00:08:44,200 Confidence. Therefore here for this. 236 00:08:44,200 --> 00:08:47,166 Minimum confidence we will. Set it equal to oh. 237 00:08:47,166 --> 00:08:48,366 Point two. 238 00:08:48,366 --> 00:08:50,500 Okay. Once again no rule of thumb. 239 00:08:50,500 --> 00:08:53,766 You can try different values depending on your business requirements. 240 00:08:54,366 --> 00:08:54,966 All right. 241 00:08:54,966 --> 00:08:56,066 Then next. 242 00:08:56,066 --> 00:08:58,200 Parameter I'm sure you guessed it as well. 243 00:08:58,200 --> 00:09:01,066 That is this time the minimum lift. 244 00:09:01,066 --> 00:09:02,233 You know that other. 245 00:09:02,233 --> 00:09:03,300 Metric which. 246 00:09:03,300 --> 00:09:06,600 Measures the quality of a rule or the relevance of a rule? 247 00:09:06,933 --> 00:09:07,466 And so now. 248 00:09:07,466 --> 00:09:09,700 According to you, what would be a good. 249 00:09:09,700 --> 00:09:10,800 Minimum lift? 250 00:09:10,800 --> 00:09:11,633 Well, that. 251 00:09:11,633 --> 00:09:14,633 Kind of decision to make, you know, you give them with experience. 252 00:09:14,733 --> 00:09:16,233 You will see through the. 253 00:09:16,233 --> 00:09:18,000 Many. Association rule. 254 00:09:18,000 --> 00:09:20,033 Learning models that you're going to build on your data. 255 00:09:20,033 --> 00:09:25,500 Sets, that generally a good lift is at least three, you know, 3456. 256 00:09:25,500 --> 00:09:27,600 7789. You know, these are. 257 00:09:27,600 --> 00:09:30,366 Good lifts, but lift below three. 258 00:09:30,366 --> 00:09:32,066 Make the rules not that relevant. 259 00:09:32,066 --> 00:09:33,533 And therefore this is kind. 260 00:09:33,533 --> 00:09:35,266 Of a rule of thumb that I'm giving you here. 261 00:09:35,266 --> 00:09:38,400 It is not based on common sense, rather based on experience. 262 00:09:38,666 --> 00:09:39,900 And therefore I recommend. 263 00:09:39,900 --> 00:09:42,966 To choose. A minimum lift. Of three. 264 00:09:43,200 --> 00:09:43,800 All right. 265 00:09:43,800 --> 00:09:46,266 And with this minimum lift we. Will get good rules. 266 00:09:46,266 --> 00:09:47,366 You know relevant rules. 267 00:09:47,366 --> 00:09:50,133 Okay. So minimum lift equals three. 268 00:09:50,133 --> 00:09:51,800 And then we have two less. 269 00:09:51,800 --> 00:09:53,800 Arguments that are. Actually very. 270 00:09:53,800 --> 00:09:55,366 Very important and in fact. 271 00:09:55,366 --> 00:09:57,200 Compulsory for our. 272 00:09:57,200 --> 00:09:59,366 Business problem. 273 00:09:59,366 --> 00:10:00,500 It has to do with the fact. 274 00:10:00,500 --> 00:10:02,600 That, you know, we want to identify. 275 00:10:02,600 --> 00:10:04,433 The best deals of by. 276 00:10:04,433 --> 00:10:06,566 One product A, and get another. 277 00:10:06,566 --> 00:10:09,966 Product B for free, and therefore the rules we. 278 00:10:09,966 --> 00:10:12,100 Want to get in the end must have. 279 00:10:12,100 --> 00:10:14,100 Only two products, one. 280 00:10:14,100 --> 00:10:17,666 Product in the left hand side of the rule and one product in the right hand 281 00:10:17,666 --> 00:10:18,700 side of. The rule. 282 00:10:18,700 --> 00:10:20,333 All right. And therefore to make sure. 283 00:10:20,333 --> 00:10:21,266 We have this, you know. 284 00:10:21,266 --> 00:10:24,000 One product A on the left and one. For a B on the right. 285 00:10:24,000 --> 00:10:26,300 Well, we need to add two more arguments here. 286 00:10:26,300 --> 00:10:29,300 Which is. First min length. 287 00:10:29,333 --> 00:10:32,266 Okay. And then max. 288 00:10:32,266 --> 00:10:32,800 Length 289 00:10:33,833 --> 00:10:34,500 where of. 290 00:10:34,500 --> 00:10:37,966 Course min length is the minimum number of elements you want to have. 291 00:10:37,966 --> 00:10:38,566 In your rule. 292 00:10:38,566 --> 00:10:39,866 You know, left or right. 293 00:10:39,866 --> 00:10:42,833 And max length is the maximum number of elements you want to. 294 00:10:42,833 --> 00:10:44,833 Have in your rule, left or right. 295 00:10:44,833 --> 00:10:45,966 And therefore here to make sure. 296 00:10:45,966 --> 00:10:47,366 We only have two. 297 00:10:47,366 --> 00:10:49,433 In our rule, you know, one on the left and one on the. 298 00:10:49,433 --> 00:10:49,966 Right. 299 00:10:49,966 --> 00:10:52,533 Well, obviously we need to set mid-length. 300 00:10:52,533 --> 00:10:53,766 To two. 301 00:10:53,766 --> 00:10:56,400 And max length same. 302 00:10:56,400 --> 00:10:57,500 To two. 303 00:10:57,500 --> 00:11:01,033 And that's only because in our business problem we want to find. 304 00:11:01,033 --> 00:11:02,500 These best deals of. 305 00:11:02,500 --> 00:11:04,100 Buying one product A and get. 306 00:11:04,100 --> 00:11:05,533 One product for free. 307 00:11:05,533 --> 00:11:09,000 Therefore our rules must have exactly two elements. 308 00:11:09,300 --> 00:11:10,533 Then imagine you wanted. 309 00:11:10,533 --> 00:11:14,866 To find the best deals of buy two products and get a third one for free. 310 00:11:15,066 --> 00:11:17,533 Then you would set min lengths to. Three. 311 00:11:17,533 --> 00:11:19,233 And max length. To three. 312 00:11:19,233 --> 00:11:20,800 And if you want to be very, very. 313 00:11:20,800 --> 00:11:23,100 Flexible on your deals, like you know, you. 314 00:11:23,100 --> 00:11:25,133 Could have deals with by one product A. 315 00:11:25,133 --> 00:11:27,900 And get one product B. For free or by two products. 316 00:11:27,900 --> 00:11:28,466 A and. 317 00:11:28,466 --> 00:11:30,000 Get one product B for free. 318 00:11:30,000 --> 00:11:33,000 Or, you know, by ten products and get one for. Free. 319 00:11:33,000 --> 00:11:34,033 Well, in this. Case you would. 320 00:11:34,033 --> 00:11:36,600 Set min lengths to two and then max length. 321 00:11:36,600 --> 00:11:37,733 To 11. 322 00:11:37,733 --> 00:11:39,933 Okay, so that really. Depends on your. Business. 323 00:11:39,933 --> 00:11:41,666 Requirements, your business problem. 324 00:11:41,666 --> 00:11:42,000 Here we. 325 00:11:42,000 --> 00:11:44,700 Just want to find the best. Deals of two products. 326 00:11:44,700 --> 00:11:47,433 By one product A, get. One product B for free and. 327 00:11:47,433 --> 00:11:47,900 That's it. 328 00:11:47,900 --> 00:11:50,933 And that's why we set min links to two and max links to two. 329 00:11:50,933 --> 00:11:51,900 So that our. Rule can. 330 00:11:51,900 --> 00:11:54,133 Have only two products. 331 00:11:54,133 --> 00:11:55,166 All right. And that's it. 332 00:11:55,166 --> 00:11:56,166 Well you know we're done. 333 00:11:56,166 --> 00:11:57,766 With this a priori. 334 00:11:57,766 --> 00:11:59,266 Function which will return the. 335 00:11:59,266 --> 00:12:02,166 Rules respecting all these values. 336 00:12:02,166 --> 00:12:03,400 We said for the parameters. 337 00:12:03,400 --> 00:12:04,366 A minimum support. 338 00:12:04,366 --> 00:12:07,366 Of 0.03, which. Means that. 339 00:12:07,400 --> 00:12:08,966 The. Products in the rules. 340 00:12:08,966 --> 00:12:12,300 Appear at least 0.3 percent of. The time. 341 00:12:12,666 --> 00:12:14,766 Then the minimum confidence, which means that. 342 00:12:14,766 --> 00:12:16,233 For each product A. 343 00:12:16,233 --> 00:12:17,266 In the left hand side. 344 00:12:17,266 --> 00:12:19,600 Of the rules, well, we will have product B in the. 345 00:12:19,600 --> 00:12:20,300 Right hand side. 346 00:12:20,300 --> 00:12:22,200 Of the rule at least 20% of the. 347 00:12:22,200 --> 00:12:24,700 Time, and then we have a minimum lift of. Three. 348 00:12:24,700 --> 00:12:27,533 And we have only two products. 349 00:12:27,533 --> 00:12:30,866 In our rules thanks to this min max equals to and max length. 350 00:12:30,866 --> 00:12:32,000 Equals two. 351 00:12:32,000 --> 00:12:33,866 All right. So are you ready. 352 00:12:33,866 --> 00:12:36,566 Are you ready to run that cell to get the rules. 353 00:12:36,566 --> 00:12:38,733 We won't have them displayed in the output. 354 00:12:38,733 --> 00:12:40,300 But don't worry we will visualize. 355 00:12:40,300 --> 00:12:42,933 Them right after this tutorial in the last. Part. 356 00:12:42,933 --> 00:12:44,100 So let's do this. 357 00:12:44,100 --> 00:12:46,900 Let's play the cell. And there we go. 358 00:12:46,900 --> 00:12:48,533 Now my friends, we have the rules.