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This being the second consecutive road game for the Eagles, and a rather substandard showing from the offensive line against the Seahawks last week, give a slight edge to the Rams. This is a very tough spot for the Eagles.

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How will they respond. After stubbing their toe in Seattle last week, the Eagles, having stayed out West, will rebound against the Rams. Have to think Carson Wentz will be juiced up (and perhaps nicely tanned.

The Rams got Jared Goff, and you can't really blame them. He's done some nice things this year. Wentz is sixth in the NFL quarterback rating, Goff ninth.

Prediction: Rams 27, Eagles 23 Eliot Shorr-Parks - Eagles Reporter, NJ Advance MediaThis is a very tough spot for the Eagles. PICK: Eagles 24, Rams 21 Darryl Slater - Jets Reporter, NJ Advance MediaAfter stubbing their toe in Seattle last week, the Eagles, having stayed out West, will rebound against the Rams.

Prediction: Eagles 30, Rams 20 nj. Hi Subscribe today for full access on your desktop, tablet, and mobile device. Already a print edition subscriber, but don't have a login. View the E-NewspaperManage your NewslettersView your Insider deals and moreMember ID CardSupportSupportLog OutLet friends in your social network know what you are reading aboutThe Buffalo Bills host the Indianapolis Colts in a Week 13 game at New Era Field. Sal Maiorana breaks down all the angles in his 3 and Out preview.

Sal Maiorana, Virginia ButlerFrank Gore (23) and Jacoby Brissett lead the Colts into Buffalo Sunday. The fact that they still have a road game at New England makes that scenario a bit unlikely, but the other three games are certainly winnable, and the first of those comes up Sunday at New Era Field when the Indianapolis Colts take up residence on the other sideline.

The Colts are one of the worst teams in the NFL, and the Bills should take care of business even with rookie quarterback Nathan Peterman expected to start. A win would get Buffalo to 7-6 with Miami in town next week before the game with the Patriots. However, the postseason dream would die Sunday if the Bills falter against Indianapolis. Can the Bills win offensively on the early downs.

Indy is allowing just 2. Buffalo, as always, will have to rely on its running game, especially with rookie Nathan Peterman most likely at quarterback in place of injured Tyrod Taylor. But if the Colts stuff the run and put the Bills in unfavorable down and distance situations, that ramps up the pressure on Peterman. The Colts are solid on the front line, but are weak at linebacker, especially with John Simon getting hurt last week and now out for the season.Each topic is composed of a set of words which are thematically related.

The words from a given topic have different probabilities for that topic.

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At the same time, each word can be attributable to one or several topics. So for example the word "sea" may be found in a topic related with sea transport but also in a topic related to holidays. Topic model automatically discards stopwords and high frequency words that occur in almost all of the documents as they don't help to determine the boundaries between topics.

Topic model's main applications include browsing, organizing and understanding large archives of documents. It can been applied for information retrieval, collaborative filtering, assessing document similarity among others.

The topics found in the dataset can also be very useful new features before applying other models like classification, clustering, or anomaly detection. Topic model returns a list of top terms for each topic found in the data. Note that topics are not labeled, so you have to infer their meaning according to the words they are composed of. By looking at each group of terms below we can interpret the first topic as regulatory related, the second as healthcare related and so on.

You can obtain up to 128 different topics. Once you build the topic model you can calculate each topic probability for a given document by using Topic Distribution. This information can be useful to find documents similarities based on their thematic. You can also list all of your topic models.

Specifies a list of terms to ignore when performing term analysis.

This can be used to change the names of the fields in the topic model with respect to the original names in the dataset or to tell BigML that certain fields should be preferred. All text fields in the dataset Specifies the fields to be considered to create the topic model. If multiple fields are given, the text field values for each row will be concatenated so that each row is still considered to be one document. If it is unset, it will be chosen automatically based on the number documents (i.

The minimum value is 2 and maximum value is 64. Example: "MySample" tags optional Array of Strings A list of strings that help classify and index your topic model. Computation is linear with respect to this parameter. The minimum value is 128 and maximum value is 16384. The minimum value is 1 and maximum value is 128. Example: true You can also use curl to customize a new topic model. Once a topic model has been successfully created it will have the following properties. Topic Model Status Creating a topic model is a process that can take just a few seconds or a few days depending on the size of the dataset used as input and on the workload of BigML's systems.

The topic model goes through a number of states until its fully completed. Through the status field in the topic model you can determine when the topic model has been fully processed and ready to be used to create predictions. Thus when retrieving a topicmodel, it's possible to specify that only a subset of fields be retrieved, by using any combination of the following parameters in the query string (unrecognized parameters are ignored): Fields Filter Parameters Parameter TypeDescription fields optional Comma-separated list A comma-separated list of field IDs to retrieve.

To update a topic model, you need to PUT an object containing the fields that you want to update to the topic model' s base URL. Once you delete a topic model, it is permanently deleted.

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If you try to delete a topic model a second time, or a topic model that does not exist, you will receive a "404 not found" response. However, if you try to delete a topic model that is being used at the moment, then BigML. To list all the topic models, you can use the topicmodel base URL. By default, only the 20 most recent topic models will be returned. You can get your list of topic models directly in your browser using your own username and API key with the following links.Nonlinear Relations between Variables.

Another potential source of problems with the linear (Pearson r) correlation is the shape of the relation. The possibility of such non-linear relationships is another reason why examining scatterplots is a necessary step in evaluating every correlation. What do you do if a correlation is strong but clearly nonlinear (as concluded from examining scatterplots). Unfortunately, there is no simple answer to this question, because there is no easy-to-use equivalent of Pearson r that is capable of handling nonlinear relations.

If the curve is monotonous (continuously decreasing or increasing) you could try to transform one or both of the variables to remove the curvilinearity and then recalculate the correlation. Another option available if the relation is monotonous is to try a nonparametric correlation (e. However, nonparametric correlations are generally less sensitive and sometimes this method will not produce any gains.

Unfortunately, the two most precise methods are not easy to use and require a good deal of "experimentation" with the data. Therefore you could:Exploratory Examination of Correlation Matrices. A common first step of many data analyses that involve more than a very few variables is to run a correlation matrix of all variables and then examine it for expected (and unexpected) significant relations.

For example, by definition, a coefficient significant at the. There is no "automatic" way to weed out the "true" correlations. This issue is general and it pertains to all analyses that involve "multiple comparisons and statistical significance.

Pairwise Deletion of Missing Data. Only this way will you get a "true" correlation matrix, where all correlations are obtained from the same set of observations. However, if missing data are randomly distributed across cases, you could easily end up with no "valid" cases in the data set, because each of them will have at least one missing data in some variable.

The most common solution used in such instances is to use so-called pairwise deletion of missing data in correlation matrices, where a correlation between each pair of variables is calculated from all cases that have valid data on those two variables.

However, it may sometimes lead to serious problems. For example, a systematic bias may result from a "hidden" systematic distribution of missing data, causing different correlation coefficients in the same correlation matrix to be based on different subsets of subjects.

In addition to the possibly biased conclusions that you could derive from such "pairwise calculated" correlation matrices, real problems may occur when you subject such matrices to another analysis (e. Thus, if you are using the pairwise method of deleting the missing data, be sure to examine the distribution of missing data across the cells of the matrix for possible systematic "patterns.

If the pairwise deletion of missing data does not introduce any systematic bias to the correlation matrix, then all those pairwise descriptive statistics for one variable should be very similar. However, if they differ, then there are good reasons to suspect a bias. For example, if the mean (or standard deviation) of the values of variable A that were taken into account in calculating its correlation with variable B is much lower than the mean (or standard deviation) of those values of variable A that were used in calculating its correlation with variable C, then we would have good reason to suspect that those two correlations (A-B and A-C) are based on different subsets of data, and thus, that there is a bias in the correlation matrix caused by a non-random distribution of missing data.

Pairwise Deletion of Missing Data vs. Another common method to avoid loosing data due to casewise deletion is the so-called mean substitution of missing data (replacing all missing data in a variable by the mean of that variable).

Mean substitution offers some advantages and some disadvantages as compared to pairwise deletion. Its main advantage is that it produces "internally consistent" sets of results ("true" correlation matrices). The main disadvantages are:Spurious Correlations. There is a third variable (the initial size of the fire) that influences both the amount of losses and the number of firemen. If you "control" for this variable (e. The main problem with spurious correlations is that we typically do not know what the "hidden" agent is.I suggest this to all my friends, which is why I'm even posting this up.

Its a morning tea and every other night you drink your night tea. Its simple and effective. Which is my favorite thing about it) Araitz HarmensFeeling pretty unhappy with how we had began to look after a couple of heavy months celebrating birthdays etc.

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I finally decided to try Skinnymint after a lot of hesitation, since I wasn't sure if a teatox would really work. But it helped me stay energized throughout my day and stay on my meal plan. And the detox tea was a great way to relax before bed. I noticed my bloat go down almost immediately and looking at my before and after pictures amazes myself.

I will definitely be using Skinnymint throughout the rest of my transformation. It takes a lot for me to post these pictures as I'm very self conscious of my stomach after two boys and two c-sections. I loved this tea and can't wait to do it again. I hardly worked out during the 28 days and did not watch what I ate so all in all I'm very happy. Thanks so much teatox!.

I just finished my first detox that began during spring break after spending a majority of this year pursuing unhealthily eating habits. Though there wasn't a drastic improvement physically, it led me on a path towards a happier and healthier lifestyle. Everyone's body is perfect, but having confidence in yourself is just as important. Be proud in your own skin and pursue that happy, healthy lifestyle. My stomach is flatter. I feel so much better for it too :).

Looking forward to the next 28 day teatox because now my broken ankle is pretty much healed I can start to exercise properly again, so I imagine the results will be even more amazing!. These are before and after pictures from two weeks!. Tried out skinnymint teatox not thinking it would help but it's fantastic reduced my bloating within the first day.

It helped decrease my appetite and gave me more energy. My favourite surprise was that I actually enjoyed the taste of the teas.

I really loved to start every day with a cup of their tea, not just because it tastes good, it gave me such a good feeling. I was a little bit lazy this month, but anyway my abs look more defined and my hip is thinner. I don't feel bloated and my stomach is a lot flatter. I was surprisingly amazed.You can add location information to your Tweets, such as your city or precise location, from the web and via third-party applications.

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biologique recherche p50 1970

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Report wrong graded result, spam, inappropriate language or other content. Please add a reason for your report:Here you will find all football predictions for today and football predictions for tomorrow. Probably some for the future, too.

We are here to help you to find the best football predictions for today faster - all football tips with descriptions are marked with description icon, predictions with more than 80 words are also marked with golden StakeHunters border. They have a very solid team and I think with Juventus that have strugled in defence this season both teams will score. Aston Villa have been very good at home this season while Millwall are yet to win a game away. Aston Villa to win looks like a great pick.

On top of this page, you can filter to see only free football predictions. StakeHunters will strive hard to be the best football prediction site in the world.Thank you so much for the 5 star rating and we're happy to have your business. Yes No Share on Facebook Share on Twitter They got the job done on time JOHN K.

Read More Business ResponseThank you for the positive feedback, John. We're grateful for your business and hope to serve you again. Yes No Share on Facebook Share on Twitter The team at Gilleland is wonderful which is one reason I came back to purchase another vehicle.

Read More Business ResponseSheila, it was so nice having you back in. We appreciate the continued business and thank you for the 5 star rating. Yes No Share on Facebook Share on Twitter I had a wonderful first time experience at gilleland and I will definitely be shopping there in the future. Read More Business ResponseTravis, we're so glad we were able to help you get your new Tahoe. Thank you for your business and we look forward to seeing you again soon.

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Read More Business ResponseThank you so much, Irene. It was a pleasure doing business with you. Yes No Share on Facebook Share on Twitter Awesome. Mike Anderson as well as Cory Anderson went above and beyond in helping me with financial and vehicle decisions. Read More Business ResponseKathleen, we're happy we could help you find your new Trax.

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We appreciate the positive review and rating and look forward to future encounters. Yes No Share on Facebook Share on Twitter Great people. Read More Business ResponseWe appreciate this, Matthew. It was a pleasure having you in and thank you for the 5 stars. Yes No Share on Facebook Share on Twitter It was a great experience BRANDEN C.

Read More Was this review helpful. Yes No Share on Facebook Share on Twitter I had service done on my pickup, communication wasn't the greatest. They found I had a bad tire, then ordered the wrong one. I wanted to know the cost and I wasn't told the correct price till I got there to pick it up. Seemed like he was too busy to explain everything and was in a big hurry. Read More Business ResponseWe appreciate the feedback, Patrick. Comments like these help us improve our services for our customers.

We apologize for any inconvenience we may caused. We value your time and business and hope to serve you in the future. Yes No Share on Facebook Share on Twitter Great. Read More Business ResponseThank you, Brooke. We're happy to have your business. Yes No Share on Facebook Share on Twitter Gilleland is the best!.

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Read More Business ResponseThank you so much, Brenda. We're grateful for your business. Yes No Share on Facebook Share on Twitter Great Service SHANE F. Read More Business ResponseWe appreciate it, Shane.In the best-case scenario, you already know everything on this list.

It can be hard to figure out the right questions to ask or remember some of the big things you may have forgotten to cover in your audit. Get our weekly newsletter from SEJ's Founder Loren Baker about the latest news in the industry. The Beginner's Guide to SEO and Illustrated Guide to Link Building. FREE SEO Tools That Deliver Results. Improve your website rankings with SEO PowerSuite. Get all the tools you need - for free. Get your free copy of SEO PowerSuite now!. Here's how you can get one for your website.

This definitive guide from a seasoned expert will help you save time and get over tech-related issues faster. If you've ever been tempted to cut back on sugar but can't face going cold turkey, Davina's realistic approach will have you shunning the sweet stuff in no time. Over the last year, sugar's effect on our health has been well documented in a constant stream of damning research.

The sweet stuff is now food enemy number one and is to blame for far more than hyperactive children and tooth decay. Television presenter and fitness guru, Davina McCall is keen to get the nation talking about sugar and here she shares her realistic tips and personal journey to becoming sugar-freeAs of today, how long have you been sugar-free.

I had given up sugar for a couple of years previously, but then when I did my Sport Relief challenge I started eating it again. I was doing an awful lot of exercise and had to eat a lot of sugar in the form of liquid gels and carbohydrates - such as rice and pasta - to keep my energy up. What was it that made you decide to give up sugar.

When my sister got cancer, the nutritionist told me that she should give up sugar and I found that quite telling. I did some research and realised I was a slave to it. Stop eating it and you stop mood swings, bad skin and weight gain. Did it make you grumpy. I was more prepared this time round though, and have, for the most part, managed to taper off my sweet tooth. Sugar-free to me means a diet free of refined sugar - things like processed foods and white flours, rice and bread. Has quitting sugar changed the way you think about food.

I used to get stuck making the same 10 meals. Also, spelt or barley make delicious alternatives to risotto rice. What health benefits did you notice after giving up sugar.

It definitely had an impact on my energy levels and my skin looks loads better. It took a while to get to that point but was worth the wait. What were the hardest times when you gave up sugar. How did you beat the cravings. Just something to give me a sweet hit.



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