[
https://issues.apache.org/jira/browse/SOLR-9252?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Joel Bernstein updated SOLR-9252:
---------------------------------
Description:
This ticket adds two new streaming expressions: *features* and *train*
These two functions work together to train a logistic regression model on text,
from a training set stored in a SolrCloud collection.
The syntax is as follows:
{code}
train(collection1, q="*:*",
features(collection1,
q="*:*",
field="tv_text",
outcome="out_i",
positiveLabel=1,
numTerms=100),
field="tv_text",
outcome="out_i",
maxIterations=100)
{code}
The *features* function extracts the feature terms from a training set using
*information gain* to score the terms.
http://www.jiliang.xyz/publication/feature_selection_for_classification.pdf
The *train* function uses the extracted features to train a logistic regression
model on a text field in the training set.
For both *features* and *train* the training set is defined by a query. The doc
vectors in the *train* use tf-idf to represent the terms in the document. The
idf is calculated for the specific training set so, multiple training sets can
be stored in the same collection without polluting the idf.
In the *train* function a batch gradient descent approach is used to
iteratively train the model.
Both the *features* and the *train* function are embedded in Solr using the
AnalyticsQuery framework. So only the model is transported across the network
with each iteration.
Both the features and the models can be stored in a SolrCloud collection. Using
this approach Solr can hold millions of models which can be selectively
deployed.
Below is the final iteration of a model trained on the Enron Ham/Spam dataset.
The model includes the terms and their idfs and weights as well a
classification evaluation describing the accuracy of model on the training set.
{code}
{
"idfs_ds": [1.2627703388716238, 1.2043595767152093,
1.3886172425360304, 1.5488587854881268, 1.6127302558747882, 2.1359177807201526,
1.514866246141212, 1.7375701403808523, 1.6166175299631897, 1.756428159015249,
1.7929202354640175, 1.2834893120635762, 1.899442866302021, 1.8639061320252337,
1.7631697575821685, 1.6820002892260415, 1.4411352768194767, 2.103708877350535,
1.2225773869965861, 2.208893321170597, 1.878981794430681, 2.043737027506736,
2.2819184561854864, 2.3264563106163885, 1.9336117619172708, 2.0467265663551024,
1.7386696457142692, 2.468795829515302, 2.069437610615317, 2.6294363202479327,
3.7388303845193307, 2.5446615802900157, 1.7430797961918219, 3.0787440662202736,
1.9579702057493114, 2.289523055570706, 1.5362003886162032, 2.7549569891263763,
3.955894889757158, 2.587435396273302, 3.945844553903657, 1.003513057076781,
3.0416264032637708, 2.248395764146843, 4.018415246738492, 2.2876164773001246,
3.3636289340509933, 1.2438124251270097, 2.733903579928544, 3.439026951535205,
0.6709665389201712, 0.9546224358275518, 2.8080115520822657, 2.477970205791343,
2.2631561797299637, 3.2378087608499606, 0.36177021415584676,
4.1083634834014315, 4.120197941048435, 2.471081544796158, 2.4241455557775633,
2.923393626201111, 2.9269972337044097, 3.2987413118451183, 2.383498249003407,
4.168988105217867, 2.877691472720256, 4.233526626355437, 3.8505343740993316,
2.3264563106163885, 2.6429318017228174, 4.260555298743357, 3.0058372954121855,
3.8688835127675283, 3.021585652380325, 3.0295538220295017, 1.9620882623582288,
3.469610374907285, 3.945844553903657, 3.4821105376715167, 4.3169082352944885,
2.520329479630485, 3.609372317282444, 3.070375816549757, 4.220281399605417,
3.9866665484239117, 3.6165408067610563, 3.788840805093992, 4.392131656532076,
4.392131656532076, 2.837281934382379, 3.698984475972131, 4.331507034715641,
2.360699334038601, 2.7368842080666815, 3.730733174286711, 3.1991566064156816,
4.4238803548466565, 2.4665153268165767, 3.175736332207583, 3.2378087608499606,
4.376627469996111, 3.3525177086259226, 3.28315658082842, 4.156565585219309,
1.6462639699299098, 2.673278958112109, 4.331507034715641, 3.955894889757158,
2.7764631943473397, 3.0497565293470212, 1.79060004880832, 3.6237610547345436,
1.6244377066690232, 2.948895919012047, 3.175736332207583, 2.850571166501062,
4.073677925413541, 2.725014632511298, 3.1573871935393867, 4.562030693327474,
3.5403794457954922, 4.580722826339627, 4.580722826339627, 3.189722574182323,
3.1665196771026594, 3.3306589148134234, 1.9745451708435238, 3.3306589148134234,
2.795272526304836, 3.3415285870503273, 4.407880013500216, 4.4238803548466565,
2.6902285164258823, 3.668212817305377, 4.543681554659277, 2.559550192783766,
1.5452257206382456, 2.2631561797299637, 4.659194441781121, 3.2678110111537597,
3.878185905429842, 3.3525177086259226, 3.374865007317919, 3.780330115426083,
4.376627469996111, 3.433020927474993, 3.6758174166905966, 4.288334862850433,
3.2378087608499606, 4.490571729345329, 2.9269972337044097, 4.029226162842708,
3.0538465145985465, 4.440140875718437, 3.533734903076824, 4.659194441781121,
4.659194441781121, 4.525663049156599, 3.706827653433157, 3.1172927363375087,
4.490571729345329, 2.552078177945065, 2.087985282971078, 4.83744267318744,
4.562030693327474, 4.09666744363824, 4.659194441781121, 1.802255192400069,
4.599771021310321, 3.788840805093992, 4.8621352857778115, 4.6798137289838575,
4.376627469996111, 3.272900080661231, 3.8970543897342247, 4.638991734463602,
4.638991734463602, 4.813345121608379, 4.813345121608379, 4.8621352857778115,
4.83744267318744, 3.588170109631841, 4.13217413209515, 4.599771021310321,
4.331507034715641, 3.134914337687328, 4.525663049156599, 4.722373343402653,
3.955894889757158, 4.967495801435638, 4.580722826339627, 4.967495801435638,
4.9134285801653625, 4.887453093762102, 4.407880013500216, 4.246949646687578,
2.198385343572182, 1.5963758750107606, 4.007719957621744],
"alpha_d": 7.150861416624748E-4,
"terms_ss": ["enron", "2000", "cc", "hpl", "daren",
"http", "gas", "forwarded", "pm", "ect", "hou", "thanks", "meter", "2001",
"attached", "deal", "am", "farmer", "your", "nom", "corp", "more", "mmbtu",
"xls", "here", "j", "let", "volumes", "questions", "www", "2004", "sitara",
"no", "money", "01", "volume", "know", "best", "meds", "bob", "prescription",
"please", "online", "file", "viagra", "02", "stop", "me", "nomination", "v",
"on", "i", "click", "texas", "03", "prices", "for", "paliourg", "php", "09",
"contract", "fyi", "actuals", "u", "04", "pain", "713", "drugs", "microsoft",
"email", "robert", "cialis", "melissa", "investment", "teco", "pat", "11",
"save", "professional", "world", "biz", "flow", "dollars", "noms", "2005",
"act", "remove", "results", "soft", "xp", "mary", "80", "spam", "following",
"06", "software", "n", "dealer", "08", "ena", "offer", "sex", "products",
"special", "compliance", "see", "free", "cheap", "html", "07", "gary", "000",
"low", "our", "houston", "many", "april", "size", "r", "tap", "lots",
"product", "pills", "xanax", "vance", "ami", "chokshi", "12", "clynes",
"ticket", "counterparty", "super", "thousand", "daily", "offers", "weight",
"05", "all", "call", "photoshop", "julie", "stock", "lisa", "steve", "million",
"health", "site", "quality", "stocks", "link", "featured", "net",
"international", "most", "investing", "works", "readers", "uncertainties",
"differ", "news", "david", "seek", "31", "only", "1933", "creative", "windows",
"subscribers", "should", "adobe", "security", "1934", "valium", "brand",
"visit", "action", "canon", "pharmacy", "sexual", "inherent", "construed",
"assumptions", "internet", "mobile", "risks", "wide", "smith", "ex", "pill",
"states", "projections", "medications", "predictions", "anticipates",
"deciding", "events", "advice", "now", "com", "browser"],
"iteration_i": 100,
"weights_ds": [0.9524452699893067, -2.9257423290160225,
-2.122240862520573, -0.40259380863176036, -1.242508927269482,
-2.1933952666745924, 0.9119553386109202, -1.3359582128074137,
-1.1717690853817335, -0.9029380383621088, -1.970576222154978,
-0.9180539343040344, -2.031736167842155, -1.382820037232718,
-1.4296530557007743, -1.5015080966872794, -0.852373483913152,
-0.2883706803921614, -0.2366741375717678, 0.2966401203916763,
-0.6792566685980972, -0.18912751254722837, 0.10265566994945839,
-1.0065678789783332, -0.8967357570889625, 0.041722607774742765,
-0.2832721589409925, -0.400560390908784, -0.6945385025086017,
-0.8488391208665993, -0.31851465800191403, 1.570768257518063,
-1.5144615060332418, 0.9411280928801138, 0.738478999511349,
-0.6875177906594712, -0.47841730767672286, -0.20502227184813,
0.4858041557455349, 1.389551367014946, -0.8886199496843126, 0.8029699876855549,
-0.7760217032166719, 0.40175437931353053, -0.6231018791954438,
1.0261571991645586, -0.44254206613371744, 0.31955072203529183,
-0.24171600421157927, -0.632533557090375, 0.774533771979748,
-1.1164595912116915, -0.2954704188664946, 0.27653823698423186,
-1.157867306631878, -5.49332153268076E-5, 0.6916900118076985,
-1.305726586870522, 1.370623007467874, 1.1100575515185573, 0.40953153124448194,
-0.4273267120664356, -0.5536271317082946, -0.03575915648164506,
0.20475308352558616, -0.2919021960690356, 1.1094392826383312,
-1.24904822249928, 1.038764158800864, 0.10525284214114823, 0.1973739189626828,
-0.33283870614700184, 1.0555375704790861, 0.25856879498650104,
0.921918816504445, -0.15711181528461088, -0.3594966291171786,
-0.6659758614594922, -0.3342439009175488, 0.3592708173532555,
0.12872616265365205, 1.362140022970902, -0.2699930594417464,
0.7449118829650243, -0.12665949567352622, 1.1289376146405283,
0.1653713075673579, 0.7008424353370497, 0.47095485852014707, 1.021689093687625,
1.0049928692400525, -0.18114402652386635, 0.4403400905532737,
1.0570966104647033, -1.167541821576636, -0.4428853975686944,
0.20694894484760668, 0.15472835818468766, 1.0009582999260647,
0.013730849275970687, -0.3882888402977611, 0.14102499499877702,
1.1560852477692065, -0.822855520787489, -0.1468595831916683,
0.9069870716505091, -0.18884872126960675, -0.19213990843838719,
-0.0032534107278622496, 0.2715800337813452, 0.0888346122807297,
-0.37031213468904256, -0.07224227291981163, 0.08850381657180348,
0.20501283264716516, -0.5852130122059844, 0.11807896760332989,
-1.3196626232666966, 0.5324969558412787, 0.7667504164777665,
0.11805357030082002, 1.0020954114301253, -0.10885082229805468,
1.003094962524753, 1.0000914796917044, 0.0094959191513861, -0.5127276009526891,
0.059129413669497796, -0.49311249434449955, 0.34652229330274653,
-0.7618731785587705, -0.3514318991274448, 0.7742232232987654,
0.7575763908124484, -0.25192129997930635, -0.24220187762559128,
1.0014232005812307, -0.3453736248293833, -0.1121687186012911,
-0.15547543099631278, 1.0840890597241875, -0.2879034857435273,
-0.227656977034567, -0.3716602841157388, 0.18007113168986144,
0.8297688092273079, 1.405797209837956, 0.3921445898278919, 1.079363745455813,
-0.6253022693091732, 0.33155358331572704, 0.9644709831096733,
-0.19686285814583682, 1.1069098903214452, -0.19597970694899214,
-0.29329229099344734, -0.037185151648282316, 1.0010206696926418,
1.0096586146138415, 0.9523090849946898, 0.34253175617551923, -0.41826608329006,
0.7213729935258942, -0.47416007242000024, 0.3210039942978008, 1.0,
0.9772041721907345, 0.2533596337281238, 0.9839657417973666,
-0.7583308570783015, 0.9476391050914625, 0.2534925274818649, 1.0,
1.0001125385832383, 0.37796474985487505, 0.3839828352290301,
0.44224405246124543, 1.046072941713049, 1.1205405856642119, 0.9165436674154628,
0.9586701268580604, 1.0000000000000968, 0.9860828147022696,
-0.32499900116244823, 1.1624049652694368, 0.4966278258894532,
-0.14840111822378488, 0.15131204240736265, 1.114787005544689,
1.1782663102351227, 0.21291210471466848, 1.0000000000385034,
0.9564718923455356, 1.0110628413440756, 1.000156375636503, 0.9763045864950046,
0.2630059727829917, 0.24199402427272665, 0.2736018381908099,
-0.7673296746900424, -0.1899398724099395],
"field_s": "body",
"trueNegative_i": 3570,
"falseNegative_i": 35,
"falsePositive_i": 75,
"error_d": 176.8112932306374,
"truePositive_i": 1381,
"id": "model_100"
}
{code}
was:
This ticket adds two new streaming expressions: *features* and *train*
These two functions work together to train a logistic regression model on text,
from a training set stored in a SolrCloud collection.
The syntax is as follows:
{code}
train(collection1, q="*:*",
features(collection1,
q="*:*",
field="tv_text",
outcome="out_i",
positiveLabel=1,
numTerms=100),
field="tv_text",
outcome="out_i",
maxIterations=100)
{code}
The *features* function extracts the feature terms from a training set using
*information gain* to score the terms.
http://www.jiliang.xyz/publication/feature_selection_for_classification.pdf
The *train* function uses the extracted features to train a logistic regression
model on a text field in the training set.
For both *features* and *train* the training set is defined by a query. The doc
vectors in the *train* use tf-idf to represent the terms in the document. The
idf is calculated for the specific training set so, multiple training sets can
be stored in the same collection without polluting the idf.
In the *train* function a batch gradient descent approach is used to
iteratively train the model.
Both the *features* and the *train* function are embedded in Solr using the
AnalyticsQuery framework. So only the model is transported across the network
with each iteration.
Both the features and the models can be stored in a SolrCloud collection. Using
this approach Solr can hold millions of models which can be selectively
deployed.
> Feature selection and logistic regression on text
> -------------------------------------------------
>
> Key: SOLR-9252
> URL: https://issues.apache.org/jira/browse/SOLR-9252
> Project: Solr
> Issue Type: Improvement
> Security Level: Public(Default Security Level. Issues are Public)
> Components: search, SolrCloud, SolrJ
> Reporter: Cao Manh Dat
> Assignee: Joel Bernstein
> Labels: Streaming
> Fix For: 6.2
>
> Attachments: SOLR-9252.patch, SOLR-9252.patch, SOLR-9252.patch,
> SOLR-9252.patch, SOLR-9252.patch, SOLR-9252.patch, SOLR-9252.patch,
> SOLR-9252.patch, SOLR-9252.patch, SOLR-9252.patch
>
>
> This ticket adds two new streaming expressions: *features* and *train*
> These two functions work together to train a logistic regression model on
> text, from a training set stored in a SolrCloud collection.
> The syntax is as follows:
> {code}
> train(collection1, q="*:*",
> features(collection1,
> q="*:*",
> field="tv_text",
> outcome="out_i",
> positiveLabel=1,
> numTerms=100),
> field="tv_text",
> outcome="out_i",
> maxIterations=100)
> {code}
> The *features* function extracts the feature terms from a training set using
> *information gain* to score the terms.
> http://www.jiliang.xyz/publication/feature_selection_for_classification.pdf
> The *train* function uses the extracted features to train a logistic
> regression model on a text field in the training set.
> For both *features* and *train* the training set is defined by a query. The
> doc vectors in the *train* use tf-idf to represent the terms in the document.
> The idf is calculated for the specific training set so, multiple training
> sets can be stored in the same collection without polluting the idf.
> In the *train* function a batch gradient descent approach is used to
> iteratively train the model.
> Both the *features* and the *train* function are embedded in Solr using the
> AnalyticsQuery framework. So only the model is transported across the network
> with each iteration.
> Both the features and the models can be stored in a SolrCloud collection.
> Using this approach Solr can hold millions of models which can be selectively
> deployed.
> Below is the final iteration of a model trained on the Enron Ham/Spam
> dataset. The model includes the terms and their idfs and weights as well a
> classification evaluation describing the accuracy of model on the training
> set.
> {code}
> {
> "idfs_ds": [1.2627703388716238, 1.2043595767152093,
> 1.3886172425360304, 1.5488587854881268, 1.6127302558747882,
> 2.1359177807201526, 1.514866246141212, 1.7375701403808523,
> 1.6166175299631897, 1.756428159015249, 1.7929202354640175,
> 1.2834893120635762, 1.899442866302021, 1.8639061320252337,
> 1.7631697575821685, 1.6820002892260415, 1.4411352768194767,
> 2.103708877350535, 1.2225773869965861, 2.208893321170597, 1.878981794430681,
> 2.043737027506736, 2.2819184561854864, 2.3264563106163885,
> 1.9336117619172708, 2.0467265663551024, 1.7386696457142692,
> 2.468795829515302, 2.069437610615317, 2.6294363202479327, 3.7388303845193307,
> 2.5446615802900157, 1.7430797961918219, 3.0787440662202736,
> 1.9579702057493114, 2.289523055570706, 1.5362003886162032,
> 2.7549569891263763, 3.955894889757158, 2.587435396273302, 3.945844553903657,
> 1.003513057076781, 3.0416264032637708, 2.248395764146843, 4.018415246738492,
> 2.2876164773001246, 3.3636289340509933, 1.2438124251270097,
> 2.733903579928544, 3.439026951535205, 0.6709665389201712, 0.9546224358275518,
> 2.8080115520822657, 2.477970205791343, 2.2631561797299637,
> 3.2378087608499606, 0.36177021415584676, 4.1083634834014315,
> 4.120197941048435, 2.471081544796158, 2.4241455557775633, 2.923393626201111,
> 2.9269972337044097, 3.2987413118451183, 2.383498249003407, 4.168988105217867,
> 2.877691472720256, 4.233526626355437, 3.8505343740993316, 2.3264563106163885,
> 2.6429318017228174, 4.260555298743357, 3.0058372954121855,
> 3.8688835127675283, 3.021585652380325, 3.0295538220295017,
> 1.9620882623582288, 3.469610374907285, 3.945844553903657, 3.4821105376715167,
> 4.3169082352944885, 2.520329479630485, 3.609372317282444, 3.070375816549757,
> 4.220281399605417, 3.9866665484239117, 3.6165408067610563, 3.788840805093992,
> 4.392131656532076, 4.392131656532076, 2.837281934382379, 3.698984475972131,
> 4.331507034715641, 2.360699334038601, 2.7368842080666815, 3.730733174286711,
> 3.1991566064156816, 4.4238803548466565, 2.4665153268165767,
> 3.175736332207583, 3.2378087608499606, 4.376627469996111, 3.3525177086259226,
> 3.28315658082842, 4.156565585219309, 1.6462639699299098, 2.673278958112109,
> 4.331507034715641, 3.955894889757158, 2.7764631943473397, 3.0497565293470212,
> 1.79060004880832, 3.6237610547345436, 1.6244377066690232, 2.948895919012047,
> 3.175736332207583, 2.850571166501062, 4.073677925413541, 2.725014632511298,
> 3.1573871935393867, 4.562030693327474, 3.5403794457954922, 4.580722826339627,
> 4.580722826339627, 3.189722574182323, 3.1665196771026594, 3.3306589148134234,
> 1.9745451708435238, 3.3306589148134234, 2.795272526304836,
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> "million", "health", "site", "quality", "stocks", "link", "featured", "net",
> "international", "most", "investing", "works", "readers", "uncertainties",
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> "windows", "subscribers", "should", "adobe", "security", "1934", "valium",
> "brand", "visit", "action", "canon", "pharmacy", "sexual", "inherent",
> "construed", "assumptions", "internet", "mobile", "risks", "wide", "smith",
> "ex", "pill", "states", "projections", "medications", "predictions",
> "anticipates", "deciding", "events", "advice", "now", "com", "browser"],
> "iteration_i": 100,
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> "field_s": "body",
> "trueNegative_i": 3570,
> "falseNegative_i": 35,
> "falsePositive_i": 75,
> "error_d": 176.8112932306374,
> "truePositive_i": 1381,
> "id": "model_100"
> }
> {code}
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