data_questions/Median_4.csv

,Question,Label
0,What do different features contribute?,8
1,Show me what the system would predict on [another instance].,64
2,What was the result when other people used the system?,44
3,What should be changed about the system?,49
4,Is feature X used or not used for the predictions?,6
5,How often does the system make mistakes?,62
6,What is the system's overall logic?,2
7,How to change this feature to get a different prediction?,12
8,What are the biases of the data?,26
9,What features does the system consider?,3
10,Does this model use this feature X?,6
11,What features does the system consider?,3
12,What features of this instance lead to the system's prediction?,69
13,What is the highest feature one can have to still get the same prediction?,20
14,Why did you ignore that data?,35
15,What algorithm is being used?,1
16,Why are instance A and instance B given the same prediction?,68
17,What features does the system consider?,3
18,What does using this feature achieve?,37
19,How precise are the predictions?,60
20,How will the system improve over time?,30
21,Give me the reason for this prediction.,67
22,How precise are the predictions?,60
23,How did you arrive at this number?,67
24,How were the ground-truth produced?,27
25,What are the most predictive rules?,4
26,What kind of data does the system learn from?,21
27,What is the definition of ML terminology?,43
28,What type of output does the system give?,50
29,What is the minimum value of feature one must have to still get this prediction?,17
30,What will the system adapt over time?,30
31,How is the output used for other system component(s)?,53
32,What will the system change over time?,30
33,How were the ground truth given?,27
34,What are the drawbacks of this dataset?,25
35,Where did you get this data from?,21
36,What are the conditions for the same prediction?,15
37,What kind of data does the system learn from?,21
38,What do you mean by ML terminology?,43
39,What is the scope of the system's capability?Can it do [A]?,51
40,How should I interpret this result in terms of bias?,26
41,What kind of instance gets this prediction?,13
42,What kind of instance gets a different prediction?,14
43,How will the accuracy/precision/recall improve?,30
44,Why does it not use this feature?,34
45,What is the system's overall logic?,2
46,How did you get this result?,67
47,What is the weakness of the data?,25
48,Why are instances A and B given different predictions?,73
49,Why is this instance predicted P instead of Q?,71
50,Which algorithm does X use?,1
51,How is the output used for other system component(s)?,53
52,How will the system adapt over time?,30
53,What kind of data does the system learn from?,21
54,What are the conditions that must be met to guarantee this result?,16
55,What features of this instance lead to the system's prediction?,69
56,What is the reason for adaptation?,30
57,Where did the data come from?,21
58,How does the system weigh different features?,8
59,How does it weigh different features?,8
60,How will the system performance improve over time?,30
61,What will cause the system to learn?,30
62,Why do you use this feature?,37
63,What features of this instance lead to the system's prediction?,69
64,How were the labels produced?,27
65,What are the top rules it uses?,4
66,How were the labels generated?,27
67,What is the lowest feature one can have to still get the same prediction?,17
68,What is the importance of each feature?,8
69,How accurate are the predictions?,60
70,What does the system use to make predictions?,7
71,In what conditions will this prediction be different?,15
72,How often does the system make mistakes?,62
73,What are the weights of the parameters?,10
74,Where is the system not effective?,56
75,How is not label A?,71
76,How were the ground-truth produced?,27
77,What is the scope of its capability?,51
78,Which feature is given importance?,8
79,Why is this instance predicted P instead of Q?,71
80,What does this output represent?,52
81,What characteristic of this data must be present or absent?,16
82,How can I best utilize the output of the system?,54
83,What is the reason for this prediction?,67
84,How should this Instance change to get a different prediction?,11
85,Which feature is the model using?,37
86,What kind of mistakes is the system likely to make?,55
87,What is the highest feature one can have to still get the same prediction?,20
88,What features does the system consider?,3
89,What is the justification for using that rule?,36
90,How accurate are the predictions?,60
91,How can I best utilize the output of the system?,54
92,How are the predictions made?,7
93,What are the top features it uses?,5
94,Why is this instance predicted P instead of Q?,71
95,How often does the system make mistakes?,62
96,What are the weaknesses of the system?,56
97,What kind of output does the system give?,50
98,How are the weights of the parameters set?,10
99,What are the top rules it uses?,4
100,What would the system predict if this feature of the instance changes to A?,64
101,Give me the reason why the system will improve over time.,30
102,What is the highest feature one can have to still get the same prediction?,20
103,How accurate are the predictions?,60
104,What would the system predict if this instance changes to A?,64
105,Which instance type gets this prediction?,13
106,What kind of instance gets a different prediction?,14
107,Why are instance A and instance B given the same prediction?,68
108,Under what conditions will this prediction not change?,15
109,What kind of algorithm is used?,1
110,What was type of data used?,21
111,What is the sample size?,21
112,How is label A not applied for this instance?,71
113,What kind of data is the system not using?,24
114,How should this feature change for this instance to get a different prediction?,12
115,How is the current instance given a particular prediction?,67
116,How precise are the predictions?,60
117,Why will the system change over time?,30
118,Under which circumstances will the model be wrong?,58
119,How will the prediction change over time?,30
120,What data is the model NOT using?,24
121,What features of this instance lead to the system's prediction?,69
122,Why is this instance predicted P instead of Q?,71
123,Why are instance A and B predicted differently?,73
124,What will the system do with new data?,30
125,What data is the system not using?,24
126,How often does the system make mistakes?,62
127,In what situations is the system likely to be correct?,59
128,How reliable are the predictions?,60
129,Is the system's performance good enough for [A]?,57
130,How precise are the predictions?,60
131,What is the scope of the system's capability?Can it do [A]?,51
132,How should this feature change for this instance to get a different prediction?,12
133,Tell me how the system improves over time.,30
134,Why will the result improve over time?,30
135,In what situations is the system likely to be correct?,59
136,How can I best utilize the output of the system?,54
137,Are the predictions accurate?,60
138,Why is this instance predicted P instead of Q?,71
139,Why are instances A and B given different predictions?,73
140,What are the top features it uses?,5
141,What is the sample size?,21
142,How would the system predict on [another instance]?,64
143,How does feature X impact its predictions?,6
144,Why is this instance predicted P instead of Q?,71
145,What are the required features for this prediction?,16
146,How does feature X impact its predictions?,6
147,Why is this instance predicted P instead of Q?,71
148,How do you set the parameter values?,10
149,How does feature X impact its predictions?,6
150,How should this feature change for this instance to get a different prediction?,12
151,What is the interpretation of this result?,52
152,What is the lowest feature one can have to still get the same prediction?,17
153,What are the rules that make this prediction?,0
154,When is the system likely to be wrong?,59
155,What data is the system not using?,24
156,Give me the features that need to be present or absent to deliver this prediction,16
157,How come this instance was given this prediction?,67
158,How to improve the model training?,49
159,How are the parameters set?,10
160,How is this instance given this prediction?,67
161,What are the results of other people using the system?,44
162,What data is the system not using?,24
163,Why do instances A and B get different predictions?,73
164,Why does the model make this choice?,36
165,How many instances are there like this?,29
166,What will the system change in the future?,30
167,How can I best utilize the output of the system?,54
168,How high do feature values have to be to still be predicted the same thing?,20
169,What/where is the data from?,21
170,What kind of mistakes is the system likely to make?,55
171,How does it know to apply this rule?,36
172,What are the reasons for incorrect classification?,58
173,What are the necessary conditions for this result?,16
174,How was this prediction made?,67
175,What would the system predict if this feature of the instance changes to A?,64
176,Which parts of the system improve over time?,30
177,How much is feature X used for the predictions?,6
178,What is the scope of the system's capability?Can it do [A]?,51
179,What features of this instance lead to the system's prediction?,69
180,What features of this instance lead to the system's prediction?,69
181,What is the reason given for this prediction?,67
182,Is there performance data published for this model?,44
183,Why is this data used?,38
184,What is the reason that the system will improve over time?,30
185,How does the system learn to change?,30
186,How is this prediction made?,7
187,What kind of mistakes is the system likely to make?,55
188,What are the limitations of the data?,25
189,How come this instance was given this class?,67
190,How will this system improve over time?,30
191,What are the necessary features required for this result?,16
192,How should this Instance change to get a different prediction?,11
193,What is the confidence on the prediction?,60
194,What kind of output does the system give?,50
195,How was this instance given this prediction?,67
196,What will be the change in this system after some time?,30
197,When is an instance predicted differently?,14
198,"For a given prediction, what is the highest value of feature one can have?",20
199,Please describe the conditions under which this prediction might be incorrect.,58
200,Give me an overall explanation of the system.,2
201,What kind of mistakes is the system likely to make?,55
202,How do you determine these parameters?,10
203,In what situations is the system likely to be correct?,59
204,Give me the top rules,4
205,Why does it not use this feature?,34
206,How does the system improve itself?,30
207,How were the labels made?,27
208,Is the system's performance good enough for [A]?,57
209,What features of this instance lead to the system's prediction?,69
210,What would the system predict if this feature of the instance changes to A?,64
211,How much data was used to make this prediction?,29
212,What is the lowest feature one can have to still get the same prediction?,17
213,Why did they make that prediction about this instance?,67
214,Why did the model not use this data?,35
215,What is the scope of change permitted to still get the same prediction?,15
216,What would the system predict if this instance changes to A?,64
217,What features did it use?,5
218,What are the flaws in the data?,26
219,What is the sample size?,21
220,Why is this instance predicted P instead of Q?,71
221,How is feature X used for your prediction?,6
222,Why is this instance predicted P instead of Q?,71
223,Why is this instance predicted P instead of Q?,71
224,What are the limitations of the data?,25
225,Why is A predicted A but B predicted B?,73
226,Which field is the reason for the prediction?,69
227,Why did it give this prediction?,67
228,How much experience with this type of data does the system have?,29
229,Why is A predicted to produce X but B to produce Y?,73
230,Why did you chose not to use this rule?,33
231,What features of this instance lead to the system's prediction?,69
232,What features of this instance lead to the system's prediction?,69
233,How to improve the model?,49
234,What features of this instance lead to the system's prediction?,69
235,What will happen to the system in the future?,30
236,What was the data used to create these labels?,27
237,What are the biases of the data?,26
238,What makes this instance different from the others?,67
239,How A is not the result for this instance?,71
240,What kind of mistakes is the system likely to make?,55
241,What sort of constraints are there on the data?,25
242,How was this instance given this value/category?,67
243,What must I do to improve the system?,49
244,What is the purpose of using this feature?,37
245,Give me an example of the system drifting.,30
246,Which item gets this prediction?,13
247,How is this result achieved?,7
248,Why is this instance predicted P instead of Q?,71
249,How should this Instance change to get a different prediction?,11
250,What rules does it use to make this prediction?,0
251,Give me the reason for using this data.,38
252,How is feature X used for predictions?,6
253,How were the labels created?,27
254,How is the output used by other component(s)?,53
255,Why are instance A and instance B given the same prediction?,68
256,What are the rules that generated this prediction?,0
257,How does it weigh different features?,8
258,What would the system predict for [a different instance]?,64
259,What are the results of other people using the system?,44
260,How to improve the system?,49
261,Is feature X used to make the predictions?,6
262,When is the system incorrect?,62
263,Which factors are included in the reasoning process?,2
264,How should this feature change for this instance to get a different prediction?,12
265,What was the data skew like?,26
266,Which attributes are used by the model?,3
267,Is feature X used or not used for the predictions?,6
268,Which features does it take into account?,3
269,Why did the system give this prediction?,67
270,Give me the highest feature that would give me this prediction.,20
271,Why does it not use this data?,35
272,What kind of algorithm is used?,1
273,What are the reasons for the same prediction of A and B?,68
274,Which attributes does the model use?,3
275,Why does it use this feature?,37
276,How accurate is this prediction?,60
277,How does the system become better over time?,30
278,What features of this instance lead to the system's prediction?,69
279,What is the reliability of this result?,60
280,How is this instance given this prediction?,67
281,In which way were the ground-truth created?,27
282,What are the top rules it uses?,4
283,Which data type is the model trained on?,21
284,What does ML terminology mean?,43
285,What kind of output does the system give?,50
286,What is the lowest feature one can have to still get the same prediction?,17
287,How will the model change over time?,30
288,What is the output used for?,53
289,What will happen to the system over time?,30
290,How were the ground-truth produced?,27
291,What are the limitations of the data?,25
292,What is the source of the data?,21
293,What is the scope of change permitted to still get the same prediction?,15
294,What kind of data does it learn from?,21
295,What does ML terminology mean?,43
296,Show me the scope of [the model's] work.,51
297,What are the biases of the data?,26
298,What is the type of instance getting this result?,13
299,Which instances would get a different result?,14
300,How will the system improve over time?,30
301,Why did you ignore this feature?,34
302,What is the system's overall reasoning?,2
303,How is this instance given this prediction?,67
304,What are the limitations of the data?,25
305,Why are A and B predicted differently?,73
306,Why is this instance P rather than Q?,71
307,What kind of algorithm is used?,1
308,How do other system components use the output?,53
309,How does the system learn to adapt?,30
310,From which kind of data does the system learn?,21
311,What are the necessary features present or absent to guarantee this prediction?,16
312,Which features lead to the prediction?,69
313,Why will the system adapt over time?,30
314,What is the source of the data?,21
315,How does it weigh different features?,8
316,How does the model prioritize features?,8
317,How will the system improve over time?,30
318,Why will the system adapt over time?,30
319,Why does it use this feature?,37
320,What features are related to the prediction?,69
321,Where did the labels come from?,27
322,What are the most salient rules that it uses?,4
323,How were the labels produced?,27
324,What is the smallest feature one can have to still get the same result?,17
325,How does it weigh different features?,8
326,What percentage of predictions are correct?,60
327,How does the system make predictions?,7
328,What is the scope of change permitted to still get the same prediction?,15
329,How often does it get the wrong prediction?,62
330,How are the parameters set?,10
331,What are the limitations of the system?,56
332,How is this instance not predicted A?,71
333,What was the source of the ground-truth?,27
334,What is the scope of the system's capability?Can it do [A]?,51
335,How does it weigh different features?,8
336,Why Q is not predicted but P?,71
337,What does the system output mean?,52
338,What are the necessary features present or absent to guarantee this prediction?,16
339,What would be best to use the output for?,54
340,How is this instance given this prediction?,67
341,What should I change in this instance to get a different prediction?,11
342,Why does it use this feature?,37
343,How to best avoid the mistakes made by the system.,55
344,What feature has the largest possible value for which one can still receive the same result?,20
345,Which features are considered by the model?,3
346,Why does it use this rule?,36
347,How often is the system correct?,60
348,How can I make best use of this output?,54
349,How does the system make predictions?,7
350,Give me the list/names of top features.,5
351,Why the result for this instance is P instead of Q?,71
352,How often does the system get it wrong?,62
353,What are the limitations of the system?,56
354,What is the kind of output?,50
355,How are the parameters set?,10
356,What are the most important rules?,4
357,What would the prediction of the class change to if a data point had A value of this attribute?,64
358,Why will the system improve over time?,30
359,For this prediction what is/are the highest value(s) of feature(s) which always leads to this prediction?,20
360,What is the confidence score of this prediction.,60
361,What would happen if this instance changes to A?,64
362,What kind of instance gets this prediction?,13
363,What kind of instance gets a different result?,14
364,How are these instances the same?,68
365,What is the scope of change permitted to still get the same prediction?,15
366,What kind of algorithm is this?,1
367,What kind of data does the system learn from?,21
368,How many items are considered in this result?,21
369,How is this instance not predicted A?,71
370,What data is the system not using?,24
371,What needs to change for this prediction to be different?,12
372,How is this instance given this prediction?,67
373,What is the precision of the prediction?,60
374,Why will the model change over time?,30
375,In what situations is the system likely to be incorrect?,58
376,How will the system drift over time?,30
377,What data is the system not using?,24
378,Which field of this instance led to this prediction?,69
379,Why does this instance receive P as a prediction instead of Q?,71
380,Why are instances A and B given different predictions?,73
381,How will the system change over time?,30
382,What data isn't being used by the model?,24
383,How accurate is the system?,62
384,When is the system likely to be correct?,59
385,How sure are you about this prediction?,60
386,Do you consider the system's performance as good enough for [A]?,57
387,How accurate is the prediction?,60
388,Can this system do [A]?,51
389,What should be the value of this feature in order to change the prediction,12
390,What will the system improve over time?,30
391,Why will the system improve over time?,30
392,Where is the system likely to be valid?,59
393,What should I do with the output?,54
394,How reliable are the predictions?,60
395,Why prediction P is the result for this instance?,71
396,Why do you give different prediction for A and B?,73
397,Which features are most used?,5
398,How many items are used to make this prediction?,21
399,What would the system predict for [a different instance]?,64
400,Why is input X important to this prediction?,6
401,Why Q is not the result for this instance?,71
402,What are the necessary features present or absent to guarantee this prediction?,16
403,What does feature X impact regarding predictions?,6
404,Why is this instance not a Q but a P?,71
405,How are the parameters set?,10
406,How does input X impact the model?,6
407,How should this feature change for this instance to get a different result?,12
408,What does the system output mean?,52
409,How much lower can the value of the feature be than this one and still give the same prediction?,17
410,What rules does it use?,0
411,In what situations is the system likely to be correct?,59
412,What kind of data is not used?,24
413,What are the necessary features present or absent to guarantee this prediction?,16
414,Why is this instance given this prediction?,67
415,How to improve the system?,49
416,What are the parameters of this model?,10
417,Which factors lead to this result?,67
418,Give me the results from other users.,44
419,Which kind of data is not being used?,24
420,Why are instances A and B given different predictions?,73
421,Why does it use this rule?,36
422,How much data like this is the system trained on?,29
423,What will the system change over time?,30
424,What use is the output of this system?,54
425,What is the highest feature value one can have to still get the same prediction?,20
426,What is the source of the data?,21
427,What kind of errors are likely to happen?,55
428,Why does it use this rule?,36
429,In what situations is the system likely to be incorrect?,58
430,What are the necessary features present or absent to guarantee this prediction?,16
431,How is this instance given this prediction?,67
432,If the feature of the instance changes to A  what will the system predict?,64
433,What will the system improve over time?,30
434,Is feature X used or not used for the predictions?,6
435,How much does this system know?,51
436,What data element was used to make this prediction?,69
437,What causes the system to give this prediction?,67
438,What features of this instance lead to the system's prediction?,69
439,What are the results of other people using the system?,44
440,Why does it use this data?,38
441,Why will the system improve over time?,30
442,How will the system adapt over time?,30
443,How does the system make predictions?,7
444,What could go wrong?,55
445,Which factors limit the data?,25
446,Why is this instance given this prediction?,67
447,Why will the system improve over time?,30
448,What are the necessary features present or absent to guarantee this prediction?,16
449,How can I modify this instance to get a different result?,11
450,How reliable are the predictions?,60
451,What is the nature of this output?,50
452,How is this instance given this prediction?,67
453,How will the system change over time?,30
454,What kind of instance gets a different prediction?,14
455,What is the highest feature value one can have to still get the same prediction?,20
456,In what situations is the system likely to be incorrect?,58
457,What is the system's overall logic?,2
458,Summarize some of the types of errors that might be made by this system.,55
459,How are the parameters set?,10
460,Under what conditions will the prediction be true?,59
461,What are the top rules it uses?,4
462,Why is this feature not used?,34
463,What will the system improve over time?,30
464,How were the labels produced?,27
465,How satisfied are you with the system's performance for [A]?,57
466,Which feature of this object led to this prediction?,69
467,If the value of this feature changes to A  what will the system predict?,64
468,How much data like this is the system trained on?,29
469,At what feature level does this prediction happen?,17
470,How is this instance given this prediction?,67
471,Why does it not use this data?,35
472,What is the range of change allowed before the prediction changes?,15
473,What would be the new prediction if this instance changes to A?,64
474,What are the top features it uses?,5
475,What are the biases of the data?,26
476,How many did they sample?,21
477,Why this instance has class P but Q does not?,71
478,Is feature X used or not used for the predictions?,6
479,Why is not label Q?,71
480,Why P is predicted instead of Q?,71
481,What are the weaknesses of the data?,25
482,Why are instances A and B given different predictions?,73
483,What features of this instance lead to the system's prediction?,69
484,What rules does it use?,0
485,How much data like this is the system trained on?,29
486,Why are instances A and B given different predictions?,73
487,Why does it not use this rule?,33
488,Which part of the data lead to the prediction?,69
489,What are the important properties of this instance that led to the prediction?,69
490,How to improve the system?,49
491,What characteristics of this instance led you to this prediction?,69
492,How will the system change over time?,30
493,How were the labels produced?,27
494,What biases does the data have?,26
495,Why is this instance given this prediction?,67
496,How is this instance not predicted A?,71
497,What should I be aware of while using this system?,55
498,What are the limitations of the data?,25
499,How is this instance given this prediction?,67
500,How to improve the system?,49
501,Why does it use this feature?,37
502,How will the system drift over time?,30
503,What kind of instance gets this prediction?,13
504,How does the system make predictions?,7
505,Give me the reason for this prediction.,67
506,How should the instance be changed to get a different (better or worse) prediction?,11
507,What rules does it use?,0
508,Why does it use this data?,38
509,How does feature X impact its predictions?,6
510,How were the labels produced?,27
511,How is the output used for other system component(s)?,53
512,Why do A and B have the same label?,68
513,What rules does it use?,0